Types of tobacco consumption and the oral microbiome in the United Arab Emirates Healthy Future (UAEHFS) Pilot Study

© 2018, The Author(s). Cigarette smoking alters the oral microbiome; however, the effect of alternative tobacco products remains unclear. Middle Eastern tobacco products like dokha and shisha, are becoming globally widespread. We tested for the first time in a Middle Eastern population the hypothesis that different tobacco products impact the oral microbiome. The oral microbiome of 330 subjects from the United Arab Emirates Healthy Future Study was assessed by amplifying the bacterial 16S rRNA gene from mouthwash samples. Tobacco consumption was assessed using a structured questionnaire and further validated by urine cotinine levels. Oral microbiome overall structure and specific taxon abundances were compared, using PERMANOVA and DESeq analyses respectively. Our results show that overall microbial composition differs between smokers and nonsmokers (p = 0.0001). Use of cigarettes (p = 0.001) and dokha (p = 0.042) were associated with overall microbiome structure, while shisha use was not (p = 0.62). The abundance of multiple genera were significantly altered (enriched/depleted) in cigarette smokers; however, only Actinobacillus, Porphyromonas, Lautropia and Bifidobacterium abundances were significantly changed in dokha users whereas no genera were significantly altered in shisha smokers. For the first time, we show that smoking dokha is associated to oral microbiome dysbiosis, suggesting that it could have similar effects as smoking cigarettes on oral health

Incense Burning is Associated with Human Oral Microbiota Composition

© 2019, The Author(s). Incense burning is common worldwide and produces environmental toxicants that may influence health; however, biologic effects have been little studied. In 303 Emirati adults, we tested the hypothesis that incense use is linked to compositional changes in the oral microbiota that can be potentially significant for health. The oral microbiota was assessed by amplification of the bacterial 16S rRNA gene from mouthwash samples. Frequency of incense use was ascertained through a questionnaire and examined in relation to overall oral microbiota composition (PERMANOVA analysis), and to specific taxon abundances, by negative binomial generalized linear models. We found that exposure to incense burning was associated with higher microbial diversity (p \u3c 0.013) and overall microbial compositional changes (PERMANOVA, p = 0.003). Our study also revealed that incense use was associated with significant changes in bacterial abundances (i.e. depletion of the dominant taxon Streptococcus), even in occasional users (once/week or less) implying that incense use impacts the oral microbiota even at low exposure levels. In summary, this first study suggests that incense burning alters the oral microbiota, potentially serving as an early biomarker of incense-related toxicities and related health consequences. Although a common indoor air pollutant, guidelines for control of incense use have yet to be developed

The oral fungal mycobiome: characteristics and relation to periodontitis in a pilot study

Abstract Background The oral fungal microbiome (mycobiome) is not well characterized, particularly in relation to oral diseases such as periodontal disease. We aimed to describe and compare the oral mycobiome of subjects with and without periodontal disease. Results We characterized the oral mycobiome in 30 adult subjects (15 with periodontal disease, 15 with good oral health) by sequencing the taxonomically informative pan-fungal internal transcribed spacer (ITS) gene in DNA extracted from oral wash samples. We observed at least 81 genera and 154 fungal species across all samples. Candida and Aspergillus were the most frequently observed genera (isolated from 100% of participants), followed by Penicillium (97%), Schizophyllum (93%), Rhodotorula (90%), and Gibberella (83%). Candida and Aspergillus were also the most highly abundant genera in the samples (median relative abundance = 21% and 44%, respectively). Aspergillus niger was the most highly abundant species in the samples (median relative abundance = 44%). We did not observe significant differences in overall oral mycobiome diversity or composition between participants with periodontal disease and participants with good oral health, nor did we observe significant differences in phylum through species level taxon relative abundance or carriage between the two groups. Genus Candida, previously associated with periodontal disease in culture-based studies, had higher median relative abundance in participants with periodontal disease (33.2%) compared to participants with oral health (2.2%), though the difference was not significant (p = 0.52). Additionally, within the periodontal disease group, median relative abundance of Candida increased with increasing number of permanent teeth lost (1–2 teeth lost: 3.2%; 3–4 teeth lost: 16.6%; ≥5 teeth lost: 73.9%; p = 0.11), though sample size was small for this analysis. Conclusions In this first study comprehensively characterizing the oral mycobiome of adults with periodontal disease or good oral health, we observed trends of higher Candida abundance in participants with periodontal disease, and participants with greater tooth loss. Small sample size may have limited the power to detect significant associations. Larger studies including subgingival samples may further establish the core oral mycobiome in health, and relate it to periodontal disease

Supplementary Table 1 from The Breast Microbiome in Breast Cancer Risk and Progression: A Narrative Review

Summary of findings of the reviewed studies at the family taxonomic level.</p

Comparison of the oral microbiome in mouthwash and whole saliva samples

<div><p>Population-based epidemiologic studies can provide important insight regarding the role of the microbiome in human health and disease. Buccal cells samples using commercial mouthwash have been obtained in large prospective cohorts for the purpose of studying human genomic DNA. We aimed to better understand if these mouthwash samples are also a valid resource for the study of the oral microbiome. We collected one saliva sample and one Scope mouthwash sample from 10 healthy subjects. Bacterial 16S rRNA genes from both types of samples were amplified, sequenced, and assigned to bacterial taxa. We comprehensively compared these paired samples for bacterial community composition and individual taxonomic abundance. We found that mouthwash samples yielded similar amount of bacterial DNA as saliva samples (<i>p</i> from Student’s t-test for paired samples = 0.92). Additionally, the paired samples had similar within sample diversity (<i>p</i> from = 0.33 for richness, and <i>p</i> = 0.51 for Shannon index), and clustered as pairs for diversity when analyzed by unsupervised hierarchical cluster analysis. No significant difference was found in the paired samples with respect to the taxonomic abundance of major bacterial phyla, <i>Bacteroidetes</i>, <i>Firmicutes</i>, <i>Proteobacteria</i>, <i>Fusobacteria</i>, and <i>Actinobacteria</i> (FDR adjusted q values from Wilcoxin signed-rank test = 0.15, 0.15, 0.87, 1.00 and 0.15, respectively), and all identified genera, including genus <i>Streptococcus</i> (q = 0.21), <i>Prevotella</i> (q = 0.25), <i>Neisseria</i> (q = 0.37), <i>Veillonella</i> (q = 0.73), <i>Fusobacterium</i> (q = 0.19), and <i>Porphyromonas</i> (q = 0.60). These results show that mouthwash samples perform similarly to saliva samples for analysis of the oral microbiome. Mouthwash samples collected originally for analysis of human DNA are also a resource suitable for human microbiome research.</p></div

Alpha-diversity of oral bacterial communities in the paired mouthwash-saliva samples.

<p>Bar plots of number of observed OTUs (a) and Shannon Index (b) in paired mouthwash-saliva samples in 10 subjects. These indices were calculated for 500 iterations of rarefied OTU table with minimum sequencing depth of 38,400 among all study subjects, with the average over the iterations taken for each participant. No differences were found between mouthwash and saliva samples in α-diversity (<i>p</i> from paired t-test = 0.33 for richness, and 0.51 for Shannon index).</p

Beta-diversity of oral bacterial communities in the paired mouthwash-saliva samples.

<p>Hierarchical cluster analysis using JSD distance. AU (approximately unbiased) <i>p</i>-values, the unbiased bootstrap probability, ranged from 0.97 to 1.00 for all paired samples in hierarchical cluster analysis with number of 1,000 bootstrap replications. Cluster with AU ≥ 0.95 are considered to be strongly supported by data. S01-S10 indicate study subject 1 to 10. “M” indicates mouthwash sample and “S” indicates salivary sample.</p

Drinking alcohol is associated with variation in the human oral microbiome in a large study of American adults

Abstract Background Dysbiosis of the oral microbiome can lead to local oral disease and potentially to cancers of the head, neck, and digestive tract. However, little is known regarding exogenous factors contributing to such microbial imbalance. Results We examined the impact of alcohol consumption on the oral microbiome in a cross-sectional study of 1044 US adults. Bacterial 16S rRNA genes from oral wash samples were amplified, sequenced, and assigned to bacterial taxa. We tested the association of alcohol drinking level (non-drinker, moderate drinker, or heavy drinker) and type (liquor, beer, or wine) with overall microbial composition and individual taxon abundance. The diversity of oral microbiota and overall bacterial profiles differed between heavy drinkers and non-drinkers (α-diversity richness p = 0.0059 and β-diversity unweighted UniFrac p = 0.0036), and abundance of commensal order Lactobacillales tends to be decreased with higher alcohol consumption (fold changes = 0.89 and 0.94 for heavy and moderate drinkers, p trend = 0.005 [q = 0.064]). Additionally, certain genera were enriched in subjects with higher alcohol consumption, including Actinomyces, Leptotrichia, Cardiobacterium, and Neisseria; some of these genera contain oral pathogens, while Neisseria can synthesize the human carcinogen acetaldehyde from ethanol. Wine drinkers may differ from non-drinkers in microbial diversity and profiles (α-diversity richness p = 0.048 and β-diversity unweighted UniFrac p = 0.059) after controlling for drinking amount, while liquor and beer drinkers did not. All significant differences between drinkers and non-drinkers remained after exclusion of current smokers. Conclusions Our results, from a large human study of alcohol consumption and the oral microbiome, indicate that alcohol consumption, and heavy drinking in particular, may influence the oral microbiome composition. These findings may have implications for better understanding the potential role that oral bacteria play in alcohol-related diseases