Evaluation of Buccal Cell Samples for Studies of Oral Microbiota

Updated perspectives on the contribution of the microbiome to the pathogenesis of mucositis using the MASCC/ISOO framework

Advances in the treatment of cancer have significantly improved mortality rates; however, this has come at a cost, with many treatments still limited by their toxic side effects. Mucositis in both the mouth and gastrointestinal tract is common following many anti-cancer agents, manifesting as ulcerative lesions and associated symptoms throughout the alimentary tract. The pathogenesis of mucositis was first defined in 2004 by Sonis, and almost 20 years on, the model continues to be updated reflecting ongoing research initiatives and more sophisticated analytical techniques. The most recent update, published by the Multinational Association for Supportive Care in Cancer and the International Society for Oral Oncology (MASCC/ISOO), highlights the numerous co-occurring events that underpin mucositis development. Most notably, a role for the ecosystem of microorganisms that reside throughout the alimentary tract (the oral and gut microbiota) was explored, building on initial concepts proposed by Sonis. However, many questions remain regarding the true causal contribution of the microbiota and associated metabolome. This review aims to provide an overview of this rapidly evolving area, synthesizing current evidence on the microbiota's contribution to mucositis development and progression, highlighting (i) components of the 5-phase model where the microbiome may be involved, (ii) methodological challenges that have hindered advances in this area, and (iii) opportunities for intervention.

Saliva assay: a call for methodological standardization

The oral cavity provides an ideal environment for microorganisms, including bacteria, viruses, and fungi, to flourish. Increasing attention has been focused on the connection between the oral microbiome and both oral and systemic diseases, spurring active research into the collection and analysis of specimens for healthcare purposes. Among the various methods for analyzing the oral microbiome, saliva analysis is especially prominent. Saliva samples, which can be collected non-invasively, provide information on the systemic health and oral microbiome composition of an individual. This review was performed to evaluate the current state of the relevant research through an examination of the literature and to suggest an appropriate assay method for investigating the oral microbiome. We analyzed articles published in English in SCI(E) journals after January 1, 2000, ultimately selecting 53 articles for review. Articles were identified through keyword searches in the PubMed, Embase, Cochrane, Web of Science, and CINAHL databases. Three experienced researchers conducted full-text assessments following title and abstract screening to select appropriate papers. Subsequently, they organized and analyzed the desired data. Our review revealed that most studies utilized unstimulated saliva samples for oral microbiome analysis. Of the 53 studies examined, 29 identified relationships between the oral microbiome and various diseases, such as oral disease, Behçet disease, cancer, and oral lichen planus. However, the studies employed diverse methods of collection and analysis, which compromised the reliability and accuracy of the findings. To address the limitations caused by methodological inconsistencies, a standardized saliva assay should be established.

Oral bacteriome and oral potentially malignant disorders: A systematic review of the associations

INTRODUCTION

Periodontal bacteria can infiltrate the epithelium, activate signaling pathways, induce inflammation, and block natural killer and cytotoxic cells, all of which contribute to the vicious circle of carcinogenesis. It is unknown whether oral dysbiosis has an impact on the etiology or prognosis of OPMD.

AIMS

Within this paradigm, this work systemically investigated and reported on the composition of oral microbiota in patients with oral potentially malignant disorders (OPMD) versus healthy controls.

METHODS

Observational studies that reported next generation sequencing analysis of oral tissue or salivary samples and found at least three bacterial species were included. Identification, screening, citation analysis, and graphical synthesis were carried out.

RESULTS

For oral lichen planus (OLP), the bacteria with the highest abundance were Fusobacterium, Capnocytophaga, Gemella, Granulicatella, Porphyromonas, and Rothia; for oral leukoplakia (OLK), Prevotella. Streptococci levels in OLK and OLP were lower. The usage of alcohol or smoke had no effect on the outcomes.

CONCLUSIONS

An increase in periodontal pathogenic bacteria could promote the development and exacerbation of lichen. Effective bacteriome-based biomarkers are worthy of further investigation and application, as are bacteriome-based treatments.

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.

Oral Microbiota-One Habitat or Diverse Niches? A Pilot Study of Sampling and Identification of Oral Bacterial and Fungal Biota in Patients with Type I Diabetes Mellitus Treated with Insulin Pump

OBJECTIVE

The oral microbiota is a very complex and dynamic microbial ecosystem. Alterations of its balance can result in oral and systemic diseases. We aimed to characterize the microbiota in particular niches of the oral cavity in adult type 1 diabetes patients treated with continuous infusion of insulin with insulin pump (IP). In addition, we aimed to determine optimal sites of oral microbiota sampling in studies of large research groups of patients with DM I.

DESIGN

In this pilot study, we sampled the buccal and soft palate mucosa, tongue, palatal and buccal dental surfaces and gingival pockets of adult DM I patients treated with IP.

RESULTS

In total, 23 patients were recruited. The oral microbiota was dominated by Streptococus and Neisseria, with a low incidence of cariogenic S. mutans and Lactobacillus, as well as periodontal pathogens such as Prevotella. There were significant differences in overall CFU counts of all strains, Gram-positive, Staphylococci, Streptococci and S. oralis strains between mucosal and dental surface sites. The overall CFU counts of all strains and Gram-positive strains were higher in dental sites vs. mucosal sites (both p < 0.001). CFU counts of S. oralis were significantly higher in dental sites vs. gingival pocket sites (p = 0.013). Candida species were rare. The mucosal sites on the buccae presented lower diversity and bacterial counts.

CONCLUSIONS

In the study group of adult DM I patients treated with IP, the microbiota in particular niches of the oral cavity was significantly different. Three distinct and optimally appropriate sampling sites for oral microflora were identified: buccal and palatal mucosa, dental surface and gingival pockets. The results of this study may be the basis for further studies of large groups of patients with DM I.

Taxonomic Assignment-Based Genome Reconstruction from Apical Periodontal Metagenomes to Identify Antibiotic Resistance and Virulence Factors

Primary apical periodontitis occurs due to various insults to the dental pulp including microbial infections, physical and iatrogenic trauma, whereas inadequate elimination of intraradicular infection during root canal treatment may lead to secondary apical periodontitis. We explored the complex intra-radicular microbial communities and their functional potential through genome reconstruction. We applied shotgun metagenomic sequencing, binning and functional profiling to identify the significant contributors to infection at the acute and chronic apical periodontal lesions. Our analysis revealed the five classified clusters representing Enterobacter, Enterococcus, Lacticaseibacillus, Pseudomonas, Streptococcus and one unclassified cluster of contigs at the genus level. Of them, the major contributors were Pseudomonas, with 90.61% abundance in acute conditions, whereas Enterobacter followed by Enterococcus with 69.88% and 15.42% abundance, respectively, in chronic conditions. Enterobacter actively participated in antibiotic target alteration following multidrug efflux-mediated resistance mechanisms, predominant in the chronic stage. The prediction of pathways involved in the destruction of the supportive tissues of the tooth in Enterobacter and Pseudomonas support their crucial role in the manifestation of respective disease conditions. This study provides information about the differential composition of the microbiome in chronic and acute apical periodontitis. It takes a step to interpret the role of a single pathogen, solely or predominantly, in establishing endodontic infection types through genome reconstruction following high throughput metagenomic DNA analysis. The resistome prediction sheds a new light on the therapeutic treatment guidelines for endodontists. However, it needs further conclusive research to support this outcome using a larger number of samples with similar etiological conditions, but different demographic origin.

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.

Reduced Abundance of Nitrate-Reducing Bacteria in the Oral Microbiota of Women with Future Preeclampsia

The oral microbiota can contribute to the regulation of blood pressure by increasing the availability of nitric oxide through the reduction of nitrate to nitrite, which can be converted into nitric oxide in the stomach and then enter the circulation. It is unclear if the composition of the oral microbiota is different between women who do and do not develop preeclampsia. This study aimed to compare the composition of the buccal microbiota just prior to the development of symptoms at 36 weeks gestation in 12 women who developed late-onset preeclampsia and 24 matched women who remained normotensive throughout pregnancy by 16S rRNA gene amplicon sequencing. The abundance of the nitrate-reducing Veillonella spp V. parvula and V. dispar and a subunit of nitrate reductase narH was compared using real-time PCR. The abundance of bacteria was correlated with maternal blood pressure and dietary intake of nitrate-containing vegetables. The results showed that the abundance of nitrate-reducing bacteria including Veillonella, specifically V. parvula, and Prevotella was reduced in women who developed preeclampsia. Veillonella but not Prevotella abundance was negatively correlated with maternal blood pressure. The dietary intake of nitrate-containing vegetables did not differ between the groups and was not correlated with the abundance of Veillonella. There was no difference in the abundance of the nitrate reductase subunit narH between the groups. These results suggest that the abundance of nitrate-reducing bacteria is reduced in the oral microbiota of women who later develop preeclampsia, indicating a potential pathway for prevention.

Development of a Microneedle Swab for Acquisition of Genomic DNA From Buccal Cells

A swab is a tool for obtaining buccal DNA from buccal mucus for biological analysis. The acquisition of a sufficient amount and high quality of DNA is an important factor in determining the accuracy of a diagnosis. A microneedle swab (MN swab) was developed to obtain more oral mucosal tissues non-invasively. Eight types of MN swabs were prepared with varying combinations of patterns (zigzag or straight), number of MNs, intervals of MNs, and sharpness of tips. When MN swab was applied up to 10 times, the tissue amount and DNA yield increased compared to commercial swabs. A zigzag pattern of microneedles was found to be more efficient than a straight pattern and increasing the number of microneedles in an array increased the DNA yield. The MN swab collected about twice the DNA compared to the commercial swab. In an in vivo test using mini pigs, the lower cycle threshold values of mucosal samples collected with MN swabs compared to samples collected with commercial swabs indicated that a greater amount of DNA was collected for SNP genotyping. A polymer MN swab is easy to manufacture by a single molding process, and it has a greater sampling capacity than existing commercial swabs.

Microbiome and Cancers of the Esophagus: A Review

Esophageal cancer (EC) is an aggressive malignant disease ranking amongst the leading causes of cancer deaths in the world. The two main histologic subtypes, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC), have distinct geographic and temporal patterns and risk factor profiles. Despite decades of research, the factors underlying these geo-temporal patterns are still not fully understood. The human microbiome has recently been implicated in various health conditions and disease, and it is possible that the microbiome may play an important role in the etiology of EC. Although studies of the microbiome and EC are still in their early stages, we review our current understanding of the potential links between ESCC, EAC, and bacterial communities in the oral cavity and esophagus. We also provide a summary of the epidemiology of EC and highlight some key challenges and future directions.

Bifunctional Composites for Biofilms Modulation on Cervical Restorations

Cervical composites treating root carious and noncarious cervical lesions usually extend subgingivally. The subgingival margins of composites present poor plaque control, enhanced biofilm accumulation, and cause gingival irritation. A potential material to restore such lesions should combine agents that interfere with bacterial biofilm development and respond to acidic conditions. Here, we explore the use of new bioresponsive bifunctional dental composites against mature microcosm biofilms derived from subgingival plaque samples. The designed formulations contain 2 bioactive agents: dimethylaminohexadecyl methacrylate (DMAHDM) at 3 to 5 wt.% and 20 wt.% nanosized amorphous calcium phosphate (NACP) in a base resin. Composites with no DMAHDM and NACP were used as controls. The newly formulated 5% DMAHDM-20% NACP composite was analyzed by micro-Raman spectroscopy and transmission electron microscopy. The wettability and surface-free energy were also assessed. The inhibitory effect on the in vitro biofilm growth and the 16S rRNA gene sequencing of survival bacterial colonies derived from the composites were analyzed. Whole-biofilm metabolic activity, polysaccharide production, and live/dead images of the biofilm grown over the composites complement the microbiological assays. Overall, the designed formulations had higher contact angles with water and lower surface-free energy compared to the commercial control. The DMAHDM-NACP composites significantly inhibited the growth of total microorganisms, Porphyromonas gingivalis, Prevotella intermedia/nigrescens, Aggregatibacter actinomycetemcomitans, and Fusobacterium nucleatum by 3 to 5-log (P < 0.001). For the colony isolates from control composites, the composition was typically dominated by the genera Veillonella, Fusobacterium, Streptococcus, Eikenella, and Leptotrichia, while Fusobacterium and Veillonella dominated the 5% DMAHDM-20% NACP composites. The DMAHDM-NACP composites contributed to over 80% of reduction in metabolic and polysaccharide activity. The suppression effect on plaque biofilms suggested that DMAHDM-NACP composites might be used as a bioactive material for cervical restorations. These results may propose an exciting path to prevent biofilm growth and improve dental composite restorations' life span.

Microbiota populations in supragingival plaque, subgingival plaque, and saliva habitats of adult dogs

Background

Oral diseases are common in dogs, with microbiota playing a prominent role in the disease process. Oral cavity habitats harbor unique microbiota populations that have relevance to health and disease. Despite their importance, the canine oral cavity microbial habitats have been poorly studied. The objectives of this study were to (1) characterize the oral microbiota of different habitats of dogs and (2) correlate oral health scores with bacterial taxa and identify what sites may be good options for understanding the role of microbiota in oral diseases. We used next-generation sequencing to characterize the salivary (SAL), subgingival (SUB), and supragingival (SUP) microbial habitats of 26 healthy adult female Beagle dogs (4.0 ± 1.2 year old) and identify taxa associated with periodontal disease indices.

Results

Bacterial species richness was highest for SAL, moderate for SUB, and lowest for SUP samples (p < 0.001). Unweighted and weighted principal coordinates plots showed clustering by habitat, with SAL and SUP samples being the most different from one another. Bacteroidetes, Proteobacteria, Firmicutes, Fusobacteria, Actinobacteria, and Spirochaetes were the predominant phyla in all habitats. Paludibacter, Filifactor, Peptostreptococcus, Fusibacter, Anaerovorax, Fusobacterium, Leptotrichia, Desulfomicrobium, and TG5 were enriched in SUB samples, while Actinomyces, Corynebacterium, Leucobacter, Euzebya, Capnocytophaga, Bergeyella, Lautropia, Lampropedia, Desulfobulbus, Enhydrobacter, and Moraxella were enriched in SUP samples. Prevotella, SHD-231, Helcococcus, Treponema, and Acholeplasma were enriched in SAL samples. p-75-a5, Arcobacter, and Pasteurella were diminished in SUB samples. Porphyromonas, Peptococcus, Parvimonas, and Campylobacter were diminished in SUP samples, while Tannerella, Proteocalla, Schwartzia, and Neisseria were diminished in SAL samples. Actinomyces, Corynebacterium, Capnocytophaga, Leptotrichia, and Neisseria were associated with higher oral health scores (worsened health) in plaque samples.

Conclusions

Our results demonstrate the differences that exist among canine salivary, subgingival plaque and supragingival plaque habitats. Salivary samples do not require sedation and are easy to collect, but do not accurately represent the plaque populations that are most important to oral disease. Plaque Actinomyces, Corynebacterium, Capnocytophaga, Leptotrichia, and Neisseria were associated with higher (worse) oral health scores. Future studies analyzing samples from progressive disease stages are needed to validate these results and understand the role of bacteria in periodontal disease development.

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.

The role of Saccharibacteria (TM7) in the subginival microbiome as a predictor for secondary cardiovascular events

BACKGROUND

The composition of the subgingival microbiota is of great importance in both oral and systemic diseases. However, a possible association of the oral microbiome and cardiovascular (CV) outcome has not yet been considered in a complex model. The primary objective of the study (DRKS-ID: DRKS00015776) was to assess differences in complex subgingival bacterial composition, depending on the CV outcome in patients undergoing Coronary Artery Bypass Grafting Surgery (CABG).

MATERIAL AND METHODS

We conducted a longitudinal cohort study enrolling 102 CV patients. After a one-year follow-up, the postoperative outcome was evaluated applying MACCE (Major Adverse Cardiac and Cerebrovascular Events) criteria. The complex oral microbiome was evaluated depending on CV outcome. The mathematical data processing included Qiime 2 software workflow and DADA2 pipeline as well as Human Oral Microbiome Database (HOMD) and Greengenes database classification. For identifying biomarkers distinguishing patients suffering from secondary CV events, the Cox Proportional Hazard Model for survival analysis was applied.

RESULTS

In total, 19,418 Operational Taxonomic Units (OTU) were mapped according to the HOMD and Greengenes database. No significant differences in alpha and beta diversity were linked to CV outcomes (Shannon index; Principal Coordinates Analysis). No biomarker predicting secondary CV events were identified applying the area under the receiver operating characteristic curve (AUC) model. However, in survival analysis, one biomarker of Saccharibacteria phylum (class: TM7-3, order: CW040, family: F16) was associated with the incidence of a secondary CV event (p = 0.016).

CONCLUSIONS

For the first time, a subgingival biomarker has been identified that supports a cardiovascular prognosis in CV patients undergoing coronary artery bypass grafting.

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.

Home sampling is a feasible method for oral microbiota analysis for infants and mothers

OBJECTIVES

Large longitudinal cohort studies in infants are needed to understand oral microbiome maturation in relation to general health. The logistics of such studies are complex and costs involved high. Methods like home sampling by caretakers might be a solution to these issues. This study aimed to evaluate feasibility of home sampling by caretakers and to assess which oral niche provides the most reliable sample.

METHODS

In this cross-sectional study 30 mothers and their infants aged 2-15 months participated. Swabs of the tongue, buccal mucosa, saliva, and dental plaque of the mother and the infant were collected by the mother after watching an instruction video. Thereafter, the trained researcher repeated the sample collection. Variations on the sampling protocol were listed. Bacterial DNA was quantified and microbial composition was assessed using 16S rDNA amplicon sequencing.

RESULTS

None of the sampled niches appeared to be unfeasible based on interviews and observed variations on protocol. No significant differences in bacterial DNA concentration between operators (mother and researcher) were found. In infant's saliva, Shannon diversity of samples collected by the researcher was significantly higher than those collected by mothers (p = 0.0009) and the bacterial composition was influenced by variations on sampling protocol (p = 0.01).

CONCLUSIONS

Home sampling by caretakers is a feasible method for oral sample collection in infants and mothers. Oral samples collected by mothers resemble samples collected by a trained researcher, with the tongue sample being the most similar and saliva the least.

CLINICAL SIGNIFICANCE

Home sampling can simplify longitudinal oral microbiota collection.

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.

Defining the oral microbiome by whole-genome sequencing and resistome analysis: the complexity of the healthy picture

Background

The microbiome of the oral cavity is the second-largest and diverse microbiota after the gut, harboring over 700 species of bacteria and including also fungi, viruses, and protozoa. With its diverse niches, the oral cavity is a very complex environment, where different microbes preferentially colonize different habitats. Recent data indicate that the oral microbiome has essential functions in maintaining oral and systemic health, and the emergence of 16S rRNA gene next-generation sequencing (NGS) has greatly contributed to revealing the complexity of its bacterial component. However, a detailed site-specific map of oral microorganisms (including also eukaryotes and viruses) and their relative abundance is still missing. Here, we aimed to obtain a comprehensive view of the healthy oral microbiome (HOM), including its drug-resistance features.

Results

The oral microbiome of twenty healthy subjects was analyzed by whole-genome sequencing (WGS) and real-time quantitative PCR microarray. Sampled oral micro-habitat included tongue dorsum, hard palate, buccal mucosa, keratinized gingiva, supragingival and subgingival plaque, and saliva with or without rinsing. Each sampled oral niche evidenced a different microbial community, including bacteria, fungi, and viruses. Alpha-diversity evidenced significant differences among the different sampled sites (p < 0.0001) but not among the enrolled subjects (p = 0.876), strengthening the notion of a recognizable HOM. Of note, oral rinse microbiome was more representative of the whole site-specific microbiomes, compared with that of saliva. Interestingly, HOM resistome included highly prevalent genes conferring resistance to macrolide, lincosamides, streptogramin, and tetracycline.

Conclusions

The data obtained in 20 subjects by WGS and microarray analysis provide for the first time a comprehensive view of HOM and its resistome, contributing to a deeper understanding of the composition of oral microbiome in the healthy subject, and providing an important reference for future studies, allowing to identify microbial signatures related to functional and metabolic alterations associated with diseases, potentially useful for targeted therapies and precision medicine.

Women's multisite microbial modulation during pregnancy

The composition of female microbiome varies with age, physiological and socio-behavior conditions. Also, changes in microbiome composition are observed as pregnancy progresses, especially in the vaginal site. Together with the physiological adaptations of gestation, changes in microbiome composition seem to be fundamental for proper fetal development. This study aimed at simultaneously evaluating the vaginal, gut, and oral microbiome of healthy pregnant women, and comparing it with those observed in healthy non-pregnant women of reproductive age. In a cross-sectional study, vaginal, oral and gut samples were collected from 42 pregnant and 18 non-pregnant women, and the microbiome composition was evaluated by 16S rRNA sequencing, using Illumina platform. In the pregnant group, we observed a positive correlation between Eubacterium and Akkermansia in the gut samples; between Eubacterium and Ruminococcus in the vaginal samples; and between Streptococcus and Gemella in the oral samples. Notwithstanding, we observed a negative correlation between Lactobacillus and Atopobium and between Lactobacillus and Gardnerella in vaginal microbiome. Prevotella was the only genus found in all three sites studied; however, there was no signal of bacterial influence between sites during pregnancy. These results suggest that in addition to hormonal and immunological variations during healthy pregnancy, the female body also undergoes microbiome modulation in multiple sites in order to maintain an eubiotic status.

Composition and function of oral microbiota between gingival squamous cell carcinoma and periodontitis

OBJECTIVES

Previous studies have proved that periodontitis is an independent risk factor of oral squamous cell carcinoma (OSCC) epidemiologically. Along with the important role of microbiota in the cancer process and the specific anatomical position, our study explored the microbial composition and functions in periodontitis and gingival squamous cell carcinoma (GSCC).

MATERIALS AND METHODS

GSCC patients (n = 10), matched periodontitis patients (n = 15), and healthy individuals (n = 15) were recruited. Saliva, subgingival plaque, tongue dorsum, buccal mucosa, cancerous tissue, and paracancerous tissue samples were collected. 16S rDNA amplicon sequencing and functional prediction were applied for the taxonomic analysis.

RESULTS

Periodontal pathogens occupied 46% in GSCC. Besides, the mutual operational taxonomy unites (OTU) generated from the subgingival plaque occupied 38.36% and 44.13% from saliva. Fusobacterium, Peptostreptococcus, and Prevotella were more abundant in cancerous tissues, while Streptococcus, Neisseria, and Haemophilus were more enriched in saliva or soft mucosa. PCoA exhibited similar cluster between tongue dorsum and saliva in GSCC. GSCC showed lower richness than periodontitis. In saliva and subgingival plaque, Atopobium was more prevalent in GSCC than periodontitis and controls in descending order. Lipopolysaccharide (LPS) biosynthesis increased in subgingival plaque of GSCC compared with the other two groups.

CONCLUSION

Periodontal pathogens were abundant in GSCC. Cancerous tissues harbor enriched periodontal pathogens while saliva or soft mucosa harbored more periodontal health related bacteria. A high level of Atopobium in saliva and LPS biosynthesis have the potential for increasing the risk of suffering from GSCC in individuals with periodontitis, which needs more evidence to clarify it.

The canine oral microbiome: variation in bacterial populations across different niches

BACKGROUND

Microbiota from different niches within the canine oral cavity were profiled and compared. Supragingival plaque and stimulated saliva, were collected alongside samples from the buccal and tongue dorsum mucosa, from 14 Labrador retrievers at three timepoints within a 1 month timeframe. The V3-V4 region of the 16S rRNA gene was sequenced via Illumina MiSeq.

RESULTS

Supragingival plaque microbiota had the highest bacterial diversity and the largest number of significant differences in individual taxa when compared to the other oral niches. Stimulated saliva exhibited the highest variability in microbial composition between dogs, yet the lowest bacterial diversity amongst all the niches. Overall, the bacteria of the buccal and tongue dorsum mucosa were most similar.

CONCLUSIONS

The bacterial community profiles indicated three discrete oral niches: soft tissue surfaces (buccal and tongue dorsum mucosa), hard tissue surface (supragingival plaque) and saliva. The ability to distinguish the niches by their microbiota signature offers the potential for microbial biomarkers to be identified in each unique niche for diagnostic use.

Oral microbial community composition is associated with pancreatic cancer: A case-control study in Iran

BACKGROUND

Oral microbiota may be related to pancreatic cancer risk because periodontal disease, a condition linked to multiple specific microbes, has been associated with increased risk of pancreatic cancer. We evaluated the association between oral microbiota and pancreatic cancer in Iran.

METHODS

A total of 273 pancreatic adenocarcinoma cases and 285 controls recruited from tertiary hospitals and a specialty clinic in Tehran, Iran provided saliva samples and filled out a questionnaire regarding demographics and lifestyle characteristics. DNA was extracted from saliva and the V4 region of the 16S rRNA gene was PCR amplified and sequenced on the MiSeq. The sequencing data were processed using the DADA2 plugin in QIIME 2 and taxonomy was assigned against the Human Oral Microbiome Database. Logistic regression and MiRKAT models were calculated with adjustment for potential confounders.

RESULTS

No association was observed for alpha diversity with an average of 91.11 (standard deviation [SD] 2.59) sequence variants for cases and 89.42 (SD 2.58) for controls. However, there was evidence for an association between beta diversity and case status. The association between the Bray-Curtis dissimilarity and pancreatic cancer was particularly strong with a MiRKAT P-value of .000142 and specific principal coordinate vectors had strong associations with cancer risk. Several specific taxa were also associated with case status after adjustment for multiple comparisons.

CONCLUSION

The overall microbial community appeared to differ between pancreatic cancer cases and controls. Whether these reflect differences evident before development of pancreatic cancer will need to be evaluated in prospective studies.

Comparison of the oral microbiome of patients with generalized aggressive periodontitis and periodontitis-free subjects

OBJECTIVE

The primary objectives of the study were to assess differences in complex subgingival bacterial composition between periodontitis-free persons and patients with generalized aggressive periodontitis (gAgP).

BACKGROUND

The composition of the oral microbiota plays an important role for both oral and systemic diseases. However, the complex nature of the oral microbiome and its homeostasis is still poorly understood.

MATERIAL AND METHODS

We compared the microbiome of 13 periodontitis-free persons to 13 patients with gAgP. The 16S rRNA genes were amplified, targeting the V3/V4 region using the MiSeq platform.

RESULTS

In total, 1713 different bacterial species were mapped according to the Greengenes database. Using the Shannon index, no significant differences in alpha diversity were found between the two study groups. In principal component and linear discriminant analyses, disease-specific differences in beta diversity of the microbiome composition were evaluated. Bacteroidetes, Spirochaetes, and Synergistetes were more abundant in gAgP whereas Proteobacteria, Firmicutes, and Actinobacteria were associated with a healthy periodontium. At the bacterial species level, we showed that Porphyromonas gingivalis is the strongest indicator of gAgP. Treponema denticola and Tanerella forsythia of the "red complex" as well as Filifactor alocis were among the ten best biomarkers for gAgP.

CONCLUSIONS

These results broaden our knowledge of disease-specific differences in the microbial community associated with generalized AgP. A more complex view of the composition of the oral microbiome describes the etiology of generalized AgP in more detail. These results could help to individually adapt periodontal therapy in these patients.

Comparison of Oral Collection Methods for Studies of Microbiota

BACKGROUND

A number of cohort studies have collected Scope mouthwash samples by mail, which are being used for microbiota measurements. We evaluated the stability of Scope mouthwash samples at ambient temperature and determined the comparability of Scope mouthwash with saliva collection using the OMNIgene ORAL Kit.

METHODS

Fifty-three healthy volunteers from Mayo Clinic and 50 cohort members from Bangladesh provided oral samples. One aliquot of the OMNIgene ORAL and Scope mouthwash were frozen immediately and one aliquot of the Scope mouthwash remained at ambient temperature for 4 days and was then frozen. DNA was extracted and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using the HiSeq. Intraclass correlation coefficients (ICC) were calculated.

RESULTS

The overall stability of the Scope mouthwash samples was relatively high for alpha and beta diversity. For example, the meta-analyzed ICC for the Shannon index was 0.86 (95% confidence interval, 0.76-0.96). Similarly, the ICCs for the relative abundance of the top 25 genera were generally high. The comparability of the two sample types was relatively low when measured using ICCs, but were increased by using a Spearman correlation coefficient (SCC) to compare the rank order of individuals.

CONCLUSIONS

Overall, the Scope mouthwash samples appear to be stable at ambient temperature, which suggests that oral rinse samples received by the mail can be used for microbial analyses. However, Scope mouthwash samples were distinct compared with OMNIgene ORAL samples.

IMPACT

Studies should try to compare oral microbial metrics within one sample collection type.

Comparison of the oral microbiome in mouthwash and whole saliva samples

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 (p from Student's t-test for paired samples = 0.92). Additionally, the paired samples had similar within sample diversity (p from = 0.33 for richness, and p = 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, Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria, and Actinobacteria (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 Streptococcus (q = 0.21), Prevotella (q = 0.25), Neisseria (q = 0.37), Veillonella (q = 0.73), Fusobacterium (q = 0.19), and Porphyromonas (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.

Gut Microbiota and Salivary Diagnostics: The Mouth Is Salivating to Tell Us Something

The microbiome of the human body represents a symbiosis of microbial networks spanning multiple organ systems. Bacteria predominantly represent the diversity of human microbiota, but not to be forgotten are fungi, viruses, and protists. Mounting evidence points to the fact that the "microbial signature" is host-specific and relatively stable over time. As our understanding of the human microbiome and its relationship to the health of the host increases, it is becoming clear that many and perhaps most chronic conditions have a microbial involvement. The oral and gastrointestinal tract microbiome constitutes the bulk of the overall human microbial load, and thus presents unique opportunities for advancing human health prognosis, diagnosis, and therapy development. This review is an attempt to catalog a broad diversity of recent evidence and focus it toward opportunities for prevention and treatment of debilitating illnesses.