Comparison of the oral microbiome in mouthwash and whole saliva samples

Metagenomic analysis reveals ecological and functional signatures of oral phageome associated with severe early childhood caries

OBJECTIVES

Severe early childhood caries (S-ECC) is highly prevalent, affecting children's oral health. S-ECC development is closely associated with the complex oral microbial microbiome and its microorganism interactions, such as the imbalance of bacteriophages and bacteria. Till now, little is known about oral phageome on S-ECC. Therefore, this study aimed to investigate the potential role of the oral phageome in the pathogenesis of S-ECC.

METHODS

Unstimulated saliva (2 mL) was collected from 20 children with and without S-ECC for metagenomics analysis. Metagenomics sequencing and bioinformatic analysis were performed to determine the two groups' phageome diversity, taxonomic and functional annotations. Statistical analysis and visualization were performed with R and SPSS Statistics software.

RESULTS

85.7% of the extracted viral sequences were predicted from phages, in which most phages were classified into Myoviridae, Siphoviridae, and Podoviridae. Alpha diversity decreased, and Beta diversity increased in the S-ECC phageome compared to the healthy group. The abundance of Podoviridae phages increased, and the abundance of Inoviridae, Herelleviridae, and Streptococcus phages decreased in the S-ECC group. Functional annotation revealed increased annotation on glycoside hydrolases and nucleotide metabolism, decreased glycosyl transferases, carbohydrate-binding modules, and biogenic metabolism in the S-ECC phageome.

CONCLUSIONS

Metagenomic analysis revealed reduced Streptococcus phages and significant changes in functional annotations within the S-ECC phageome. These findings suggest a potential weakening of the regulatory influence of oral bacteria, which may indicate the development of innovative prevention and treatment strategies for S-ECC. These implications deserve further investigation and hold promise for advancing our understanding and management of S-ECC.

CLINICAL SIGNIFICANCE

The findings of this study indicate that oral phageomes are associated with bacterial genomes and metabolic processes, affecting the development of S-ECC. The reduced modulatory effect of the oral phageome in counteracting S-ECC's cariogenic activity suggests a new avenue for the prevention and treatment of S-ECC.

The impact of saliva collection methods on measured salivary biomarker levels

Saliva diagnostics have become increasingly popular due to their non-invasive nature and patient-friendly collection process. Various collection methods are available, yet these are not always well standardized for either quantitative or qualitative analysis. In line, the objective of this study was to evaluate if measured levels of various biomarkers in the saliva of healthy individuals were affected by three distinct saliva collection methods: 1) unstimulated saliva, 2) chew stimulated saliva, and 3) oral rinse. Saliva samples from 30 healthy individuals were obtained by the three collection methods. Then, the levels of various salivary biomarkers such as proteins and ions were determined. It was found that levels of various biomarkers obtained from unstimulated saliva were comparable to those in chew stimulated saliva. The levels of potassium, sodium, and amylase activity differed significantly among the three collection methods. Levels of all biomarkers measured using the oral rinse method significantly differed from those obtained from unstimulated and chew-stimulated saliva. In conclusion, both unstimulated and chew-stimulated saliva provided comparable levels for a diverse group of biomarkers. However, the results obtained from the oral rinse method significantly differed from those of unstimulated and chew-stimulated saliva, due to the diluted nature of the saliva extract.

The Immune System Response to Porphyromonas gingivalis in Neurological Diseases

Previous studies have reported an association between oral microbial dysbiosis and the development and progression of pathologies in the central nervous system. Porphyromonas gingivalis (Pg), the keystone pathogen of the oral cavity, can induce a systemic antibody response measured in patients' sera using enzyme-linked immunosorbent assays. The present case-control study quantified the immune system's response to Pg abundance in the oral cavities of patients affected by different central nervous system pathologies. The study cohort included 87 participants: 23 healthy controls (HC), 17 patients with an acute neurological condition (N-AC), 19 patients with a chronic neurological condition (N-CH), and 28 patients with neurodegenerative disease (N-DEG). The results showed that the Pg abundance in the oral cavity was higher in the N-DEG patients than in the HC (p = 0.0001) and N-AC patients (p = 0.01). In addition, the Pg abundance was higher in the N-CH patients than the HCs (p = 0.005). Only the N-CH patients had more serum anti-Pg antibodies than the HC (p = 0.012). The inadequate response of the immune system of the N-DEG group in producing anti-Pg antibodies was also clearly indicated by an analysis of the ratio between the anti-Pg antibodies quantity and the Pg abundance. Indeed, this ratio was significantly lower between the N-DEG group than all other groups (p = 0.0001, p = 0.002, and p = 0.03 for HC, N-AC, and N-CH, respectively). The immune system's response to Pg abundance in the oral cavity showed a stepwise model: the response diminished progressively from the patients affected with an acute condition to the patients suffering from chronic nervous system disorders and finally to the patients affected by neurodegenerative diseases.

Salivary and fecal microbiota: potential new biomarkers for early screening of colorectal polyps

Objective

Gut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of CRC-associated microbes. Multiple studies have identified gut and fecal microbiome-derived biomarkers for precursors lesions of CRC detection. However, few studies have used salivary samples to predict colorectal polyps. Therefore, in order to find new noninvasive colorectal polyp biomarkers, we searched into the differences in fecal and salivary microbiota between patients with colorectal polyps and healthy controls.

Methods

In this case-control study, we collected salivary and fecal samples from 33 patients with colorectal polyps (CP) and 22 healthy controls (HC) between May 2021 and November 2022. All samples were sequenced using full-length 16S rRNA sequencing and compared with the Nucleotide Sequence Database. The salivary and fecal microbiota signature of colorectal polyps was established by alpha and beta diversity, Linear discriminant analysis Effect Size (LEfSe) and random forest model analysis. In addition, the possibility of microbiota in identifying colorectal polyps was assessed by Receiver Operating Characteristic Curve (ROC).

Results

In comparison to the HC group, the CP group's microbial diversity increased in saliva and decreased in feces (p < 0.05), but there was no significantly difference in microbiota richness (p > 0.05). The principal coordinate analysis revealed significant differences in β-diversity of salivary and fecal microbiota between the CP and HC groups. Moreover, LEfSe analysis at the species level identified Porphyromonas gingivalis, Fusobacterium nucleatum, Leptotrichia wadei, Prevotella intermedia, and Megasphaera micronuciformis as the major contributors to the salivary microbiota, and Ruminococcus gnavus, Bacteroides ovatus, Parabacteroides distasonis, Citrobacter freundii, and Clostridium symbiosum to the fecal microbiota of patients with polyps. Salivary and fecal bacterial biomarkers showed Area Under ROC Curve of 0.8167 and 0.8051, respectively, which determined the potential of diagnostic markers in distinguishing patients with colorectal polyps from controls, and it increased to 0.8217 when salivary and fecal biomarkers were combined.

Conclusion

The composition and diversity of the salivary and fecal microbiota were significantly different in colorectal polyp patients compared to healthy controls, with an increased abundance of harmful bacteria and a decreased abundance of beneficial bacteria. A promising non-invasive tool for the detection of colorectal polyps can be provided by potential biomarkers based on the microbiota of the saliva and feces.

Oral microbiome as a new research-target for supportive care and precision oncology

PURPOSE OF REVIEW

A growing number of studies demonstrate the oral bacterial shift in cancer patients and the enrichment of oral bacteria in distant tumours. During the oncological treatment, opportunistic oral bacteria correlate with oral toxicities. This review focused on the most recent studies to identify which genera are the most mentioned and deserved further investigation.

RECENT FINDINGS

This review evaluated bacterial changes in patients with head and neck, colorectal, lung and breast cancer. Greater composition of disease-related genera (e.g., Fusobacterium , Porphyromonas , Lactobacillus , Streptococcus , and Parvimonas ) are present in the oral cavity of these groups of patients. The tumour specimen characterisation of head and neck, pancreatic and colorectal cancer also describes the presence of oral taxa. No evidence indicates that commensal oral bacteria have protective roles in distant tumours. Regardless, oral care is critical to prevent the growth of oral pathogens and reduce infection foci.

SUMMARY

Recent evidence suggests that oral microbiota is a potential biomarker for oncological clinical outcomes and oral toxicities. Currently, the literature presents a remarkable methodological variety - from the sample collection site to the preference of the data analysis tools. For the oral microbiome to achieve the stage of being used as a clinical tool in the oncological context, more studies are necessary.

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.

Evaluation of alcohol-free mouthwash for studies of the oral microbiome

Oral bacteria play important roles in human health and disease. Oral samples collected using ethanol-containing mouthwash are widely used for oral microbiome studies. However, ethanol is flammable and not ideal for transportation/storage in large quantities, and some individuals may avoid ethanol due to the burning sensation or due to various personal, medical, religious, and/or cultural factors. Here, we compared ethanol-free and ethanol-containing mouthwashes using multiple microbiome metrics and assessed the stability of the mouthwash samples stored up to 10 days before processing. Forty volunteers provided oral wash samples collected using ethanol-free and ethanol-containing mouthwashes. From each sample, one aliquot was immediately frozen, one was stored at 4°C for 5 days and frozen, while the third aliquot was stored for 5 days at 4°C and 5 days at ambient temperature to mimic shipping delays and then frozen. DNA was extracted, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatic processing was performed using QIIME 2. Microbiome metrics measured in the two mouthwash types were very similar, with intraclass correlation coefficients (ICCs) for alpha and beta diversity metrics greater than 0.85. Relative abundances of some taxa were significantly different, but ICCs of the top four most abundant phyla and genera were high (> 0.75) for the comparability of the mouthwashes. Stability during delayed processing was also high for both mouthwashes based on alpha and beta diversity measures and relative abundances of the top four phyla and genera (ICCs ≥ 0.90). These results demonstrate ethanol-free mouthwash performs similarly to ethanol-containing mouthwash for microbial analyses, and both mouthwashes are stable for at least 10 days without freezing prior to laboratory processing. Ethanol-free mouthwash is suitable for collecting and shipping oral wash samples, and these results have important implications for planning future epidemiologic studies of the oral microbiome.

Did you choose appropriate mouthwash for managing chemoradiotherapy-induced oral mucositis? The therapeutic effect compared by a Bayesian network meta-analysis

Background

Oral mucositis (OM) is one of the most common adverse effects of radiotherapy and chemotherapy. It greatly affects the patients' quality of life and hinders cancer treatment implementation. Treating OM with mouthwash is a widely used strategy that can effectively relieve symptoms and promote healing. However, the wide mouthwash selection confuses clinicians. This Bayesian network meta-analysis aimed to compare the effects of various mouthwash types used to treat OM and provide high-level evidence-based recommendations for OM treatment.

Methods

Database search included PubMed, Embase, Cochrane Library, and Web of Science from inception to April 21, 2022. The primary outcome was OM score improvement following the World Health Organization grades. The randomized controlled trial (RCT) bias risk assessment tool provided in the Cochrane Handbook assessed the studies' risk of bias. We performed pairwise and Bayesian network meta-analysis with random effects following the PRISMA guideline.

Results

The study included 13 RCTs with 570 patients. Pairwise comparisons showed that povidone-iodine was more effective than chlorhexidine (weighted mean difference [WMD], -2.64; 95% confidence interval [CI], -2.72 to -2.56) but inferior to granulocyte-macrophage colony-stimulating factor (GM-CSF; WMD, 0.20; 95% CI, 0.06-0.34) after one week of mouthwash treatment. Vitamin E (WMD, -0.94; 95% CI, -1.03 to -0.85), natural drugs (WMD, -0.93; 95% CI, -1.46 to -0.40), and phenytoin (WMD, -0.38; 95% CI, -0.59 to -0.17) exhibited better therapeutic effects than a placebo after three weeks of treatment. Bayesian network meta-analysis showed that povidone-iodine was superior to chlorhexidine in treating OM (WMD, 2.63; 95% CI, 0.20-5.01). Other mouthwashes showed no significant differences. Rank probability indicated that the best OM therapeutic mouthwashes were GM-CSF (54%), vitamin E (24%), and natural drugs (43%) after one, two, and three weeks of treatment, respectively.

Conclusion

GM-CSF was the most effective mouthwash type for OM treatment. When considering the cost and effectiveness, povidone-iodine and sodium bicarbonate might be the most advantageous. Furthermore, natural drugs have the same potential in treating OM. Safety and acceptability are their most outstanding characteristic.

Elevated dietary carbohydrate and glycemic intake associate with an altered oral microbial ecosystem in two large U.S. cohorts

The human oral microbiome is associated with chronic diseases including cancer. However, our understanding of its relationship with diet is limited. We assessed the associations between carbohydrate and glycemic index (GI) with oral microbiome composition in 834 non-diabetic subjects from the NCI-PLCO and ACS-CPSII cohorts. The oral microbiome was characterized using 16Sv3-4 rRNA-sequencing from oral mouthwash samples. Daily carbohydrate and GI were assessed from food frequency questionnaires. We used linear regression, permutational MANOVA, and negative binomial Generalized Linear Models (GLM) to test associations of diet with α- and β-diversity and taxon abundance (adjusting for age, sex, cohort, BMI, smoking, caloric intake, and alcohol). A q-value (FDR-adjusted P-value) of <0.05 was considered significant. Oral bacterial α-diversity trended higher in participants in the highest quintiles of carbohydrate intake, with marginally increased richness and Shannon diversity (p-trend=0.06 and 0.07). Greater carbohydrate intake was associated with greater abundance of class Fusobacteriia (q=0.02) and genus Leptotrichia (q=0.01) and with lesser abundance of an Actinomyces OTU (q=4.7E-04). Higher GI was significantly related to greater abundance of genus Gemella (q=0.001). This large, nationwide study provides evidence that diets high in carbohydrates and GI may influence the oral microbiome.

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.

Salivary Porphyromonas gingivalis predicts outcome in oral squamous cell carcinomas: a cohort study

Background

Studies suggest Porphyromonas gingivalis (Pg) increased the incidence of oral squamous cell carcinoma (OSCC). However, fimA genotypes distribution of Pg, the origination of Pg in tissue, and its prognostic value are inconclusive. We aimed to investigate the frequency of fimA genotypes in OSCC patients, study the association between Pg and OSCC, and explore the prognostic value of Pg.

Methods

The abundance of Pg in saliva from the OSCC group and the OSCC-free group was analysed by qPCR. The presence of Pg was explored in OSCC tissue and para-cancerous tissue by in situ hybridization. The frequency of fimA genotypes in saliva and OSCC tissue was determined by PCR, then PCR products were sequenced and compared. Clinical data were extracted, and patients followed up for a median period of 23 months. Clinicopathological variables were compared with the abundance of Pg using Pearson Chi-square test or Fisher’s exact test. The disease-free survival (DFS) rate was calculated by Kaplan–Meier method with log-rank tests.

Results

Comparing the OSCC-free group, 95 patients with OSCC showed a high abundance of Pg in saliva (P = 0.033), and OSCC tissue showed strong in situ expression of Pg compared with paired normal tissue. Patients with OSCC showed a dominant distribution of Pg with genotype I + Ib (21.1%), II (31.6%), and IV (21.1%). FimA genotypes detected in saliva were in accordance with those in OSCC tissue, there was, moreover, a significant similarity in amplified Pg fragments. Of the 94 responsive OSCC patients, the recurrence rate was 26.6% (25/94). Overabundance of Pg in saliva showed advanced pathologic staging (P = 0.008), longer disease-free time (P = 0.029) and lower recurrence rate (P = 0.033). The overabundance of Pg in saliva was associated with improved disease-free survival (P = 0.049).

Conclusions

This study indicated that Pg might involve in the pathogenesis of OSCC, Pg carrying fimA I, Ib, II, and IV were prevalent genotypes in patients with OSCC, the provenance of Pg in OSCC tissue might be from the salivary microbial reservoir, and the abundance of Pg in saliva might consider as a favorable potential prognostic indicator in OSCC.

Molecular Dynamic Simulation Search for Possible Amphiphilic Drug Discovery for Covid-19

To determine whether quaternary ammonium (k21) binds to Severe Acute Respiratory Syndrome–Coronavirus 2 (SARS-CoV-2) spike protein via computational molecular docking simulations, the crystal structure of the SARS-CoV-2 spike receptor-binding domain complexed with ACE-2 (PDB ID: 6LZG) was downloaded from RCSB PD and prepared using Schrodinger 2019-4. The entry of SARS-CoV-2 inside humans is through lung tissues with a pH of 7.38–7.42. A two-dimensional structure of k-21 was drawn using the 2D-sketcher of Maestro 12.2 and trimmed of C18 alkyl chains from all four arms with the assumption that the core moiety k-21 was without C18. The immunogenic potential of k21/QA was conducted using the C-ImmSim server for a position-specific scoring matrix analyzing the human host immune system response. Therapeutic probability was shown using prediction models with negative and positive control drugs. Negative scores show that the binding of a quaternary ammonium compound with the spike protein’s binding site is favorable. The drug molecule has a large Root Mean Square Deviation fluctuation due to the less complex geometry of the drug molecule, which is suggestive of a profound impact on the regular geometry of a viral protein. There is high concentration of Immunoglobulin M/Immunoglobulin G, which is concomitant of virus reduction. The proposed drug formulation based on quaternary ammonium to characterize affinity to the SARS-CoV-2 spike protein using simulation and computational immunological methods has shown promising findings.

Pancreatic Cancer Meets Human Microbiota: Close Encounters of the Third Kind

Simple Summary

The microorganisms colonizing the epithelial surfaces of the human body, called microbiota, have been shown to influence the initiation, progression and response to therapy of many solid tumors, including pancreatic ductal adenocarcinoma, the most prominent form of pancreatic cancer. Here, we summarize the current knowledge about the influence of oral, gut and intratumoral microbiota on pancreatic ductal adenocarcinoma development and chemoresistance.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal types of cancer with a dismal prognosis. The five-year survival rate has not changed significantly in over 40 years. Current first-line treatments only offer a modest increase in overall survival in unselected populations, and there is an urgent need to personalize treatment in this aggressive disease and develop new therapeutic strategies. Evolving evidence suggests that the human microbiome impacts cancerogenesis and cancer resistance to therapy. The mechanism of action and interaction of microbiome and PDAC is still under investigation. Direct and indirect effects have been proposed, and the use of several microbiome signatures as predictive and prognostic biomarkers for pancreatic cancer are opening new therapeutic horizons. In this review, we provide an overview for the clinicians of studies describing the influence and associations of oral, gastrointestinal and intratumoral microbiota on PDAC development, progression and resistance to therapy and the potential use of microbiota as a diagnostic, prognostic and predictive biomarker for PDAC.

Optimizing the quality of clinical studies on oral microbiome: A practical guide for planning, performing, and reporting

With this review, we aim to increase the quality standards for clinical studies with microbiome as an output parameter. We critically address the existing body of evidence for good quality practices in oral microbiome studies based on 16S rRNA gene amplicon sequencing. First, we discuss the usefulness of microbiome profile analyses. Is a microbiome study actually the best approach for answering the research question? This is followed by addressing the criteria for the most appropriate study design, sample size, and the necessary data (study metadata) that should be collected. Next, we evaluate the available evidence for best practices in sample collection, transport, storage, and DNA isolation. Finally, an overview of possible sequencing options (eg, 16S rRNA gene hypervariable regions, sequencing platforms), processing and data interpretation approaches, as well as requirements for meaningful data storage, sharing, and reporting are provided.

Increasing Reproducibility in Oral Microbiome Research

Evidence on the role of the oral microbiome in health and disease is changing the way we understand, diagnose, and treat ailments. Numerous studies on diseases affecting the oral cavity have revealed a large amount of data that is invaluable for the advancements in diagnosing and treating these diseases. However, the clinical translation of most of these exploratory data is stalled by variable methodology between studies and non-uniform reporting of the data.Understanding the key areas that are gateways to bias in microbiome studies is imperative to overcome this challenge faced by oral microbiome research. Bias can be multifactorial and may be introduced in a microbiome research study during the formulation of the study design, sample collection and storage, or the sample processing protocols before sequencing. This chapter summarizes the recommendations from literature to eliminate bias in the microbiome research studies and to ensure the reproducibility of the microbiome research data.

Comparison of Periodontopathic Bacterial Profiles of Different Periodontal Disease Severity Using Multiplex Real-Time Polymerase Chain Reaction

Periodontopathic bacteria are known to have a pivotal role in the pathogenesis of periodontitis. The aim of the study was to quantitatively compare bacterial profile of patients with different severity of periodontal disease using samples from mouthwash and the subgingival area. Further analysis was performed to evaluate the correlation between mouthwash and two subgingival sampling methods: paperpoint and gingival retraction cord; 114 subjects enrolled in the study, and were divided equally into three groups according to disease severity. Mouthwash and subgingival sampling were conducted, and the samples were quantitatively analyzed for 11 target periodontopathic bacteria using multiplex real-time PCR. There were statistically significant differences in bacterial counts and prevalence of several species between the study groups. Mouthwash sampling showed significant correlations with two different subgingival sampling methods in regard to the detection of several bacteria (e.g., ρ = 0.793 for Porphyromonas gingivalis in severe periodontitis), implying that mouthwash sampling can reflect subgingival microbiota. However, the correlation was more prominent as disease severity increased. Although bacteria in mouthwash have potential to become a biomarker, it may be more suitable for the diagnosis of severe periodontitis, rather than early diagnosis. Further research is required for the discovery of biomarkers for early diagnosis of periodontitis.

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.

Study on the Salivary Microbial Alteration of Men With Head and Neck Cancer and Its Relationship With Symptoms in Southwest China

This study explored the association between oral microbes and head and neck cancer (HNC) as well as symptoms related to patients with HNC before surgical treatment. Fifty-six patients with HNC and 64 matched healthy controls were recruited from West China hospital in Southwest China. The demographic, clinical, and symptom data were collected. Salivary samples were collected to determine the microbial characteristics using 16S rRNA gene sequencing. Patients with HNC presented increased Capnocytophaga abundances. The oral microbial markers as Capnocytophaga (area under the curve=0.81) achieved a high classification power between the HNC patients and healthy controls. Moreover, using Capnocytophaga in conjunction with symptom of voice/speech difficulty achieved an overall predicting accuracy of 92.5% comparing with using Capnocytophaga alone (79.2% accuracy) in distinguishing the HNC patients from healthy controls. Salivary microbial profiles and HNC symptoms may be potential biomarkers for HNC screening.

Taxonomic profiling and functional characterization of the healthy human oral bacterial microbiome from the north Indian urban sub-population

Poor oral health has broad consequences that can be seen at personal as well as societal levels, especially in developing countries like India. We have limited information on the healthy oral cavity's inhabitant microorganisms that play a crucial role in overall oral health. In a comprehensive culture-independent approach, the bacterial composition of healthy human oral cavities was determined from a sub-population of northern India. During this study, 20 mouthwash-derived metagenomes were explored for identifying bacterial diversity using the 16S rRNA hypervariable V3 region with the MiSeq Illumina platform. On the taxonomy assignment of operational taxonomic units (OTUs), 20 assigned phyla and 162 genera were recovered among the participants. The mean relative abundance revealed that Streptococcus was the dominant genera among the participants. However, at inter-individual analysis, Neisseria and Haemophilus exhibited first-order dominance among five and three healthy individuals, respectively. Correlation studies indicate that Streptococcus shares a strong relationship with Rothia, Corynebacterium, Prevotella, and Veillonella, whereas it was negatively correlated with Neisseria, Aggregatibacter, Porphyromonas, and Fusobacteria like Gram-negative bacteria. Bacterial diversity showed insignificant differences at the level of age and gender within and between the participants. The results support several of the major findings of previous reports on the healthy oral microbiome of the Indian population, however, the present investigation further illustrates that demographic region leaves an impact on overall bacterial composition. The study will assist in a better understanding of the oral microbiome from region-specific Indian population that was otherwise highly under-represented.

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.

Modulation of pathogenic oral biofilms towards health with nisin probiotic

Background

Oral dysbiosis is an imbalance in the oral microbiome and is associated with a variety of oral and systemic diseases, including periodontal disease, caries, and head and neck/oral cancer. Although antibiotics can be used to control this dysbiosis, they can lead to adverse side effects and superinfections. Thus, novel strategies have been proposed to address these shortcomings. One strategy is the use of probiotics as antimicrobial agents, since they are considered safe for humans and the environment. Specifically, the Gram-positive Lactococcus lactis, a species present in the oral and gut microbiota, is able to produce nisin, which has been used worldwide for food preservation.

Objective

The objective of this study was to test whether a nisin probiotic can promote a healthier oral microbiome in pathogen-spiked oral biofilms.

Results

We found that L. lactis can prevent oral biofilm formation and disrupt 24-h and 48-h pre-formed biofilms. Finally, we demonstrate that both treatments, a nisin-producing L. lactis probiotic and nisin can decrease the levels of pathogens in the biofilms and return the diversity levels back to control or ‘healthy’ levels.

Conclusion

A nisin-producing probiotic, can be used to treat ‘disease-altered’ biofilms and promote healthier oral biofilms, which may be useful for improving patient oral health.

1H-NMR-Based salivary metabolomics from females with temporomandibular disorders - A pilot study

Although temporomandibular disorder (TMD) is the second most common musculoskeletal disorder in the general population, the disease is multifactorial and presents symptoms common to other conditions which misdiagnosis can lead to treatment failure. In this case-control study, we performed, for the first time, a high-resolution ¹H-nuclear magnetic resonance spectroscopy metabolomic analysis of the saliva of 26 women with TMD of muscular origin (experimental group [EG]) at the beginning (EG-pre) and at the end (EG-post) of a conservative treatment, and of 27 normal women (control group [CG]) to identify a metabolic signature for TMD. One-way analysis of variance showed changes in the concentration of phenylacetate, dimethylamine, maltose, acetoin, and isovalerate. Partial least-square discriminant analysis showed that metabolite signals did not overlap in CG X EG-pre and EG-pre X EG-post, but overlapped in CG X EG-post. The area under the receiver operating characteristic curve was 1 in CG X EG-pre (95% CI, 1.000-1.000; p < 0.002), 0.993 in EG-pre X EG-post (95% CI, 0.963-1.000), and 0.832 in CG X EG-post (95% CI, 0.699-0.961). These results suggest that the metabolomic profiles of women with and without TMD differ, while after treatment there is a lower distinction and slight tendency towards overlapping between CG and EG-post compared to pre treatment. We also found that phenylacetate, dimethylamine, maltose, acetoin, and isovalerate are potential biomarkers for TMD of muscular origin.

Comparison of Oral Microbiota Collected Using Multiple Methods and Recommendations for New Epidemiologic Studies

We compared four different oral collection methods for studying the human oral microbiome: an OMNIgene ORAL kit, Scope mouthwash, nonethanol mouthwash, and Saccomanno’s fixative. Our study shows that the type of the collection method can have a large impact on the results of an oral microbiome analysis. We recommend that one consistent oral collection method should be used for all oral microbiome comparisons. While Scope and nonethanol mouthwashes are less expensive and provide results similar to those with OMNIgene, Saccomanno’s fixative may be unfavorable due to the microbial differences detected in this study. Our results will help guide the design of future oral microbiome studies.

Epidemiologic studies use various biosample collection methods to study associations between human oral microbiota and health outcomes. However, the agreement between the different methods is unclear. We compared a commercially available OMNIgene ORAL kit to three alternative collection methods: Saccomanno’s fixative, Scope mouthwash, and nonethanol mouthwash. Oral samples were collected from 40 individuals over 4 visits. Two samples were collected from each subject per visit: one with OMNIgene and one with an alternative method. DNA was extracted using the DSP DNA Virus Pathogen kit, and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using MiSeq. Oral collection methods were compared based on alpha and beta diversity metrics and phylum- and genus-level relative abundances. All alpha diversity metrics were significantly lower for Saccomanno’s fixative than for OMNIgene (P < 0.001), whereas the two mouthwashes were more similar to OMNIgene. Principal-coordinate analysis (PCoA) using the Bray-Curtis and weighted UniFrac beta diversity matrices showed large differences in the microbial compositions of samples collected with Saccomanno’s compared to those with OMNIgene and the mouthwashes. Clustering by collection method was not observed in unweighted UniFrac PCoA plots, suggesting differences in relative abundances but not specific taxa detected by the collection methods. Relative abundances of most taxa were significantly different between OMNIgene and the other methods at each taxonomic level, with Saccomanno’s showing the least agreement with OMNIgene. There were clear differences in oral microbial communities between the four oral collection methods, particularly for Saccomanno’s fixative.

IMPORTANCE We compared four different oral collection methods for studying the human oral microbiome: an OMNIgene ORAL kit, Scope mouthwash, nonethanol mouthwash, and Saccomanno’s fixative. Our study shows that the type of the collection method can have a large impact on the results of an oral microbiome analysis. We recommend that one consistent oral collection method should be used for all oral microbiome comparisons. While Scope and nonethanol mouthwashes are less expensive and provide results similar to those with OMNIgene, Saccomanno’s fixative may be unfavorable due to the microbial differences detected in this study. Our results will help guide the design of future oral microbiome studies.

The Human Oral Microbiome in Health and Disease: From Sequences to Ecosystems

Abstract: The human oral cavity is home to an abundant and diverse microbial community (i.e., the oral microbiome), whose composition and roles in health and disease have been the focus of intense research in recent years. Thanks to developments in sequencing-based approaches, such as 16S ribosomal RNA metabarcoding, whole metagenome shotgun sequencing, or meta-transcriptomics, we now can efficiently explore the diversity and roles of oral microbes, even if unculturable. Recent sequencing-based studies have charted oral ecosystems and how they change due to lifestyle or disease conditions. As studies progress, there is increasing evidence of an important role of the oral microbiome in diverse health conditions, which are not limited to diseases of the oral cavity. This, in turn, opens new avenues for microbiome-based diagnostics and therapeutics that benefit from the easy accessibility of the oral cavity for microbiome monitoring and manipulation. Yet, many challenges remain ahead. In this review, we survey the main sequencing-based methodologies that are currently used to explore the oral microbiome and highlight major findings enabled by these approaches. Finally, we discuss future prospects in the field.

Oral Microbiota as Promising Diagnostic Biomarkers for Gastrointestinal Cancer: A Systematic Review

Emerging evidence has shown the potential of oral microbiota as a noninvasive diagnostic tool in gastrointestinal (GI) cancer. PubMed, Web of Science, and Embase were systematically searched for eligible studies published until May 31, 2019. Of the 17 included studies published between 2011 and 2019, five kinds of GI cancer, including colorectal cancer (n=6), pancreatic cancer (n=5), gastric cancer (n=4), esophageal cancer (n=2) and liver cancer (n=1), were reported. Generally, the diagnostic performance of the multi-bacteria model for GI cancer was strong with the best area under the receiver operator characteristic curve (AUC) exceeding 0.90, but only one study had a validation phase. Pathogens involved in periodontal disease, such as Porphyromonas gingivalis and Tannerella forsythia, were linked to various kinds of GI cancer. Besides, more oral bacteria significantly differed between cases with upper digestive cancer and healthy controls when compared to colorectal cancer (the most common form of lower digestive cancer), probably indicating a different mechanism due to anatomical and physiological differences in the digestive tract. Oral microbiota changes were associated with risk of various kinds of GI cancer, which could be considered as a potential tool for early prediction and prevention of GI cancer, but validation based on a large population, reproducible protocols for oral microbiota research and oral-gut microbiota transmission patterns are required to be resolved in further studies.

Airway microbiome composition correlates with lung function and arterial stiffness in an age-dependent manner

Objective

To investigate age-associated changes in airway microbiome composition and their relationships with lung function and arterial stiffness among genetically matched young and elderly pairs.

Methods

Twenty-four genetically linked family pairs comprised of younger (≤40 years) and older (≥60 years) healthy participants were recruited (Total n = 48). Lung function and arterial stiffness (carotid-femoral pulse wave velocity (PWV) and augmentation index (AIx)) were assessed. Sputum samples were collected for targeted 16S rRNA gene amplicon sequencing and correlations between microbiome composition, lung function and arterial stiffness were investigated.

Results

Elderly participants exhibited reductions in lung function (FEV1 (p<0.001), FVC (p<0.001) and percentage FEV1/FVC (p = 0.003)) and a 1.3–3.9-fold increase in arterial stiffness (p<0.001) relative to genetically related younger adults. Elderly adults had a higher relative abundance of Firmicutes (p = 0.035) and lower relative abundance of Proteobacteria (p = 0.014), including specific genera Haemophilus (p = 0.024) and Lautropia (p = 0.020) which were enriched in the younger adults. Alpha diversity was comparable between young and elderly pairs (p>0.05) but was inversely associated with lung function (FEV1%Predicted and FVC %Predicted) in the young (p = 0.006 and p = 0.003) though not the elderly (p = 0.481 and p = 0.696). Conversely, alpha diversity was negatively associated with PWV in the elderly (p = 0.01) but not the young (p = 0.569). Specifically, phylum Firmicutes including the genus Gemella were correlated with lung function (FVC %Predicted) in the young group (p = 0.047 and p = 0.040), while Fusobacteria and Leptotrichia were associated with arterial stiffness (PWV) in the elderly (both p = 0.004).

Conclusion

Ageing is associated with increased Firmicutes and decreased Proteobacteria representation in the airway microbiome among a healthy Asian cohort. The diversity and composition of the airway microbiome is independently associated with lung function and arterial stiffness in the young and elderly groups respectively. This suggests differential microbial associations with these phenotypes at specific stages of life with potential prognostic implications.

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

Epidemiological studies using saliva have revealed relationships between the oral microbiome and many oral and systemic diseases. However, when collecting from a large number of participants such as a large-scale cohort study, the time it takes to collect saliva can be a problem. Mouth-rinsed water, which is water that has been used to rinse the oral cavity, can be used as an alternative method for collecting saliva for oral microbiome analysis because it can be collected in a shorter time than saliva. The purpose of this study was to verify whether mouth-rinsed water is a suitable saliva substitute for analyzing the oral microbiome. We collected samples of mouth-rinsed water, stimulated saliva, unstimulated saliva, and tongue coating from 10 systemic healthy participants, and compared the microbial diversity and composition of the samples using next-generation sequencing of 16S rRNA-encoding genes. The results showed that the microbial diversity of mouth-rinsed water was similar to that of unstimulated and stimulated saliva, and significantly higher than that of tongue-coating samples. The microbial composition at the species level of mouth-rinsed water also showed a very high correlation with the composition of unstimulated and stimulated saliva. These results suggest that the mouth-rinsed water is a suitable collection method instead of saliva for oral microbiome analysis.

Does the endometrial cavity have a molecular microbial signature?

Recent molecular studies concluded that the endometrium has a resident microbiota dominated by Lactobacillus spp. and is therefore similar to that of the vagina. These findings were largely derived from endometrial samples obtained through a transcervical catheter and thus prone to contamination. Herein, we investigated the molecular microbial profiles of mid-endometrial samples obtained through hysterectomy and compared them with those of the cervix, vagina, rectum, oral cavity, and controls for background DNA contamination. Microbial profiles were examined through 16S rRNA gene qPCR and sequencing. Universal bacterial qPCR of total 16S rDNA revealed a bacterial load exceeding that of background DNA controls in the endometrium of 60% (15/25) of the study subjects. Bacterial profiles of the endometrium differed from those of the oral cavity, rectum, vagina, and background DNA controls, but not of the cervix. The bacterial profiles of the endometrium and cervix were dominated by Acinetobacter, Pseudomonas, Cloacibacterium, and Comamonadaceae. Both 16S rRNA gene sequencing and Lactobacillus species-specific (L. iners & L crispatus) qPCR showed that Lactobacillus was rare in the endometrium. In conclusion, if there is a microbiota in the middle endometrium, it is not dominated by Lactobacillus as was previously concluded, yet further investigation using culture and microscopy is necessary.

Association of Coffee and Tea Intake with the Oral Microbiome: Results from a Large Cross-Sectional Study

Background: The oral microbiota play a central role in oral health, and possibly in carcinogenesis. Research suggests that coffee and tea consumption may have beneficial health effects. We examined the associations of these common beverages with the oral ecosystem in a large cross-sectional study.Methods: We assessed oral microbiota in mouthwash samples from 938 participants in two U.S. cohorts using 16S rRNA gene sequencing. Coffee and tea intake were assessed from food frequency questionnaires. We examined associations of coffee and tea intake with overall oral microbiota diversity and composition using linear regression and permutational MANOVA, respectively, and with taxon abundance using negative binomial generalized linear models; all models adjusted for age, sex, cohort, body mass index, smoking, ethanol intake, and energy intake.Results: Higher tea intake was associated with greater oral microbiota richness (P = 0.05) and diversity (P = 0.006), and shifts in overall community composition (P = 0.002); coffee was not associated with these microbiome parameters. Tea intake was associated with altered abundance of several oral taxa; these included Fusobacteriales, Clostridiales, and Shuttleworthia satelles (higher with increasing tea) and Bifidobacteriaceae, Bergeyella, Lactobacillales, and Kingella oralis (lower with increasing tea). Higher coffee intake was only associated with greater abundance of Granulicatella and Synergistetes.Conclusions: In the largest study to date of tea and coffee consumption in relation to the oral microbiota, the microbiota of tea drinkers differed in several ways from nondrinkers.Impact: Tea-driven changes to the oral microbiome may contribute to previously observed associations between tea and oral and systemic diseases, including cancers. Cancer Epidemiol Biomarkers Prev; 27(7); 814-21. ©2018 AACR.