Assessing the Effect of Smokeless Tobacco Consumption on Oral Microbiome in Healthy and Oral Cancer Patients

Oral cancer is a globally widespread cancer that features among the three most prevalent cancers in India. The risk of oral cancer is elevated by factors such as tobacco consumption, betel-quid chewing, excessive alcohol consumption, unhygienic oral condition, sustained viral infections, and also due to dysbiosis in microbiome composition of the oral cavity. Here, we performed an oral microbiome study of healthy and oral cancer patients to decipher the microbial dysbiosis due to the consumption of smokeless-tobacco-based products and also revealed the tobacco-associated microbiome. The analysis of 196 oral microbiome samples from three different oral sites of 32 healthy and 34 oral squamous cell carcinoma (OSCC) patients indicated health status, site of sampling, and smokeless tobacco consumption as significant covariates associated with oral microbiome composition. Significant similarity in oral microbiome composition of smokeless-tobacco-consuming healthy samples and OSCC samples inferred the possible role of smokeless tobacco consumption in increasing inflammation-associated species in oral microbiome. Significantly higher abundance of Streptococcus was found to adequately discriminate smokeless-tobacco-non-consuming healthy samples from smokeless-tobacco-consuming healthy samples and contralateral healthy site of OSCC samples from the tumor site of OSCC samples. Comparative analysis of oral microbiome from another OSCC cohort also confirmed Streptococcus as a potential marker for healthy oral microbiome. Gram-negative microbial genera such as Prevotella, Capnocytophaga, and Fusobacterium were found to be differentially abundant in OSCC-associated microbiomes and can be considered as potential microbiome marker genera for oral cancer. Association with lipopolysaccharide (LPS) biosynthesis pathway further confirms the differential abundance of Gram-negative marker genera in OSCC microbiomes.

Dynamic Alterations of Oral Microbiota Related to Halitosis in Preschool Children

Objective

This longitudinal study was aimed to evaluate the dynamic shift in oral microbiota during the process of halitosis progression among preschool children.

Methods

The oral examinations, questionnaires and tongue coating specimens were collected at the baseline and 12-month follow-up. All children were oral healthy at the enrollment. At the 12-month follow-up, children who developed halitosis were included to the halitosis group (n = 10). While children who matched the age, gender, kindergarten and without halitosis were included to the control group (n = 10). 16S rRNA gene sequencing was used to reveal the shift of the tongue coating microbiome in these children during the 12- month period with the Human Oral Microbiome Database.

Results

A remarkable shift in relative abundance of specific bacteria was observed prior to halitosis development. The principal coordinates and alpha diversity analyses revealed different shifting patterns of halitosis and the healthy participants’ microbiome structures and bacterial diversity over the 12-month follow-up. Both groups showed variable microbiota community structures before the onset of halitosis. Halitosis-enriched species Prevotella melaninogenica, Actinomyces sp._HMT_180 and Saccharibacteria TM7_G-1_bacterium_HMT_352 were finally selected as biomarkers in the halitosis-onset prediction model after screening, with a prediction accuracy of 91.7%.

Conclusions

The microbiome composition and relative abundance of the tongue coatings in the halitosis and control groups remarkably differed, even prior to the onset of the clinical manifestations of halitosis. The halitosis prediction model constructed on the basis of tongue coating microbiome biomarkers indicated the microbial shifts before the halitosis onset. Therefore, this can be considered for the timely detection and intervention of halitosis in children.

Oral Microbiome Shifts From Caries-Free to Caries-Affected Status in 3-Year-Old Chinese Children: A Longitudinal Study

As one of the most prevalent human infectious diseases, dental caries results from dysbiosis of the oral microbiota driven by multiple factors. However, most of caries studies were cross-sectional and mainly focused on the differences in the oral microbiota between caries-free (CF) and caries-affected (CA) populations, while little is known about the dynamic shift in microbial composition, and particularly the change in species association pattern during disease transition. Here, we reported a longitudinal study of a 12-month follow-up of a cohort of 3-year-old children. Oral examinations and supragingival plaque collections were carried out at the beginning and every subsequent 6 months, for a total of three time points. All the children were CF at enrollment. Children who developed caries at 6-month follow-up but had not received any dental treatment until the end of the study were incorporated into the CA group. Children who remained CF at the end of the study were incorporated into the CF group. Using Illumina Miseq Sequencing of the 16S rRNA gene, we monitored the shift of supragingival microbiome during caries initiation and progression in children who developed caries over the 12-month study period. Intriguingly, principle coordinates analyses revealed two major shifting patterns in microbial structures during caries initiation and progression in CA group, but not in CF group. Dynamic co-occurring OTU network study showed that compared to CF group, there was significant increase in both number and intensity of correlations between microbial taxa, as well as the formation of tight clusters of specific bacteria in CA group. Furthermore, there were enhanced correlations, positive ones between CA-enriched taxa, and negative ones between CF-enriched and CA-enriched species within CA group. Our data suggested coordinated microbial interactions could be essential to caries pathogenesis. Most importantly, our study indicated that significant microbial shifts occur not only during caries development, but even in the sub-clinical state. Using supragingival microbiome profiles, we were able to construct a caries-onset prediction model with a prediction accuracy of 93.1%. Our study indicated that the microbial shifts prior to the onset of caries might potentially be used for the early diagnosis and prediction of caries.