The salivary microbiome is consistent between subjects and resistant to impacts of short-term hospitalization

Microbial diagnostics in periodontal diseases

Microbial analytical methods have been instrumental in elucidating the complex microbial etiology of periodontal diseases, by shaping our understanding of subgingival community dynamics. Certain pathobionts can orchestrate the establishment of dysbiotic communities that can subvert the host immune system, triggering inflammation and tissue destruction. Yet, diagnosis and management of periodontal conditions still rely on clinical and radiographic examinations, overlooking the well-established microbial etiology. This review summarizes the chronological emergence of periodontal etiological models and the co-evolution with technological advances in microbial detection. We additionally review the microbial analytical approaches currently accessible to clinicians, highlighting their value in broadening the periodontal assessment. The epidemiological importance of obtaining culture-based antimicrobial susceptibility profiles of periodontal taxa for antibiotic resistance surveillance is also underscored, together with clinically relevant analytical approaches to guide antibiotherapy choices, when necessary. Furthermore, the importance of 16S-based community and shotgun metagenomic profiling is discussed in outlining dysbiotic microbial signatures. Because dysbiosis precedes periodontal damage, biomarker identification offers early diagnostic possibilities to forestall disease relapses during maintenance. Altogether, this review highlights the underutilized potential of clinical microbiology in periodontology, spotlighting the clinical areas most conductive to its diagnostic implementation for enhancing prevention, treatment predictability, and addressing global antibiotic resistance.

The Salivary Microbiome and Predicted Metabolite Production Are Associated with Barrett's Esophagus and High-Grade Dysplasia or Adenocarcinoma

BACKGROUND

Esophageal adenocarcinoma (EAC) is rising in incidence, and established risk factors do not explain this trend. Esophageal microbiome alterations have been associated with Barrett's esophagus (BE) and dysplasia and EAC. The oral microbiome is tightly linked to the esophageal microbiome; this study aimed to identify salivary microbiome-related factors associated with BE, dysplasia, and EAC.

METHODS

Clinical data and oral health history were collected from patients with and without BE. The salivary microbiome was characterized, assessing differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features. Microbiome metabolic modeling was used to predict metabolite production.

RESULTS

A total of 244 patients (125 non-BE and 119 BE) were analyzed. Patients with high-grade dysplasia (HGD)/EAC had a significantly higher prevalence of tooth loss (P = 0.001). There were significant shifts with increased dysbiosis associated with HGD/EAC, independent of tooth loss, with the largest shifts within the genus Streptococcus. Modeling predicted significant shifts in the microbiome metabolic capacities, including increases in L-lactic acid and decreases in butyric acid and L-tryptophan production in HGD/EAC.

CONCLUSIONS

Marked dysbiosis in the salivary microbiome is associated with HGD and EAC, with notable increases within the genus Streptococcus and accompanying changes in predicted metabolite production. Further work is warranted to identify the biological significance of these alterations and to validate metabolic shifts.

IMPACT

There is an association between oral dysbiosis and HGD/EAC. Further work is needed to establish the diagnostic, predictive, and causal potential of this relationship.

Screening of heat-killed lactic acid bacteria based on inhibitory activity against oral bacteria and effects of oral administration of heat-killed Ligilactobacillus salivarius CP3365 on periodontal health in healthy participants: a double-blinded, randomized, placebo-controlled trial

Objectives

The aims of this study were to select heat-killed lactic acid bacteria (HKL) with antibiotic activity and investigate the efficacy of this bacteria in maintaining periodontal parameters in healthy participants.

Materials and methods

An in vitro evaluation was conducted to assess the inhibitory efficacy of lactic acid bacteria against Porphyromonas gingivalis and Fusobacterium nucleatum subsp. nucleatum. The effects of HKL administration on various parameters (plaque control record, bleeding on probing, and probing pocket depth) were assessed in a randomized, placebo-controlled trial. Participants in the test and placebo groups (n = 32) consumed oral tablets containing placebo or HKL daily for 8 weeks. Oral bacteria in supra-plaque and saliva were identified using 16S rRNA gene community profiling analysis.

Results

Heat-killed Ligilactobacillus salivarius CP3365 significantly (p < 0.05) decreased the viability of oral bacteria and was selected for clinical trials. Administration of HKL CP3365 significantly (p < 0.05) inhibited increases in each parameter. No changes in the relative abundance of P. gingivalis or F. nucleatum subsp. nucleatum were detected by HKL CP3365, but the relative abundance of oral bacteria (genera Porphyromonas, Fusobacterium, and Haemophilus) was significantly (p < 0.05) decreased.

Conclusion

HKL CP3365 effectively inhibited oral bacteria growth and was useful for maintaining periodontal health.

Clinical Trial Registration

[https://www.umin.ac.jp/ctr/index.htm], identifier [UMIN000045656].

Comparative Analysis of Primers Used for 16S rRNA Gene Sequencing in Oral Microbiome Studies

Recent advances in genomic technologies have enabled more in-depth study of the oral microbiome. In this study, we compared the amplicons generated by primers targeting different sites of the 16S rRNA gene found in the Human Oral Microbiome Database (HOMD). Six sets of primer targeting V1-V2, V1-V3, V3-V4, V4-V5, V5-V7 and V6-V8 regions of 16S rRNA were tested via in silico simulation. Primers targeting the V1-V2, V3-V4, and V4-V5 regions generated more than 90% of the original input sequences. Primers targeting the V1-V2 and V1-V3 regions exhibited a low number of mismatches and unclassified sequences at the taxonomic level, but there were notable discrepancies at the species level. Phylogenetic tree comparisons showed primers targeting the V1-V2 and V3-V4 regions showed performances similar to primers targeting the whole 16s RNA region in terms of separating total oral microbiomes and periodontopathogens. In an analysis of clinical oral samples, V1-V2 primers showed superior performance for identifying more taxa and had better resolution sensitivity for Streptococcus than V3-V4 primers. In conclusion, primers targeting the V1-V2 region of 16S rRNA showed the best performance for oral microbiome studies. In addition, the study demonstrates the need for careful PCR primer selections.

The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett's Esophagus to Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barrett's esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genus Streptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L-lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.

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.

SARS-CoV-2 and Prevotella spp.: friend or foe? A systematic literature review

During this global pandemic of the COVID-19 disease, a lot of information has arisen in the media and online without scientific validation, and among these is the possibility that this disease could be aggravated by a secondary bacterial infection such as Prevotella, as well as the interest or not in using azithromycin, a potentially active antimicrobial agent. The aim of this study was to carry out a systematic literature review, to prove or disprove these allegations by scientific arguments. The search included Medline, PubMed, and Pubtator Central databases for English-language articles published 1999-2021. After removing duplicates, a total of final eligible studies (n=149) were selected. There were more articles showing an increase of Prevotella abundance in the presence of viral infection like that related to Human Immunodeficiency Virus (HIV), Papillomavirus (HPV), Herpesviridae and respiratory virus, highlighting differences according to methodologies and patient groups. The arguments for or against the use of azithromycin are stated in light of the results of the literature, showing the role of intercurrent factors, such as age, drug consumption, the presence of cancer or periodontal diseases. However, clinical trials are lacking to prove the direct link between the presence of Prevotella spp. and a worsening of COVID-19, mainly those using azithromycin alone in this indication.

Choice of 16S Ribosomal RNA Primers Impacts Male Urinary Microbiota Profiling

Accessibility to next-generation sequencing (NGS) technologies has enabled the profiling of microbial communities living in distinct habitats. 16S ribosomal RNA (rRNA) gene sequencing is widely used for microbiota profiling with NGS technologies. Since most used NGS platforms generate short reads, sequencing the full-length 16S rRNA gene is impractical. Therefore, choosing which 16S rRNA hypervariable region to sequence is critical in microbiota profiling studies. All nine 16S rRNA hypervariable regions are taxonomically informative, but due to variability in profiling performance for specific clades, choosing the ideal 16S rRNA hypervariable region will depend on the bacterial composition of the habitat under study. Recently, NGS allowed the identification of microbes in the urinary tract, and urinary microbiota has become an active research area. However, there is no current study evaluating the performance of different 16S rRNA hypervariable regions for male urinary microbiota profiling. We collected urine samples from male volunteers and profiled their urinary microbiota by sequencing a panel of six amplicons encompassing all nine 16S rRNA hypervariable regions. Systematic comparisons of their performance indicate V1V2 hypervariable regions better assess the taxa commonly present in male urine samples, suggesting V1V2 amplicon sequencing is more suitable for male urinary microbiota profiling. We believe our results will be helpful to guide this crucial methodological choice in future male urinary microbiota studies.

Comparison of Microbiome in Stimulated Saliva in Edentulous and Dentate Subjects

Measurement of saliva microbes is promoted as a way to detect oral and systemic disease, yet there is a multitude of factors that affect the oral microbiome. The salivary microbiome is influenced by biofilm of shedding (epithelial) and non-shedding (tooth) surfaces. Methods for study of the salivary microbiome are by no means standardized, and differences in sample collection, storage, and processing can all affect results to some degree. Here we describe one method of saliva collection that has been validated for reproducibility. Standard 16S rRNA gene analysis is done using the Human Oral Microbiome Database library which results in analysis that is straightforward. Everything about this procedure except the library synthesis and DNA sequencing itself can easily be done in-house. To gauge the ability of salivary microbial analytics to distinguish between edentulous and dentate oral conditions, differences in the saliva microbiome of subjects with and without teeth were examined. Fifty-two dentate and 49 edentulous subjects provided stimulated saliva samples. 16S rRNA gene sequencing, QIIME-based data processing, and statistical analysis were done using several different analytical approaches to detect differences in the salivary microbiome between the two groups. Bacteria diversity was lower in the edentulous group. Remarkably, all 31 of the most significant differences in taxa were deficits that occurred in the edentulous group. As one might expect, many of these taxa are attributed to dental plaque and gingival sulcus-associated bacteria verifying that the measurement of 16S rRNA genes in the bacteria of the saliva can be used to reproducibly measure expected differences in the oral microbiome that occur with edentulism or other conditions and diseases.

Minimal Associations between Short-Term Dietary Intake and Salivary Microbiome Composition

Background: Increasing evidence points to the esophageal microbiome as an important co-factor in esophageal neoplasia. Esophageal microbiome composition is strongly influenced by the oral microbiome. Salivary microbiome assessment has emerged as a potential non-invasive tool to identify patients at risk for esophageal cancer, but key host and environmental factors that may affect the salivary microbiome have not been well-defined. This study aimed to evaluate the impact of short-term dietary intake on salivary microbiome composition. Methods: Saliva samples were collected from 69 subjects prior to upper endoscopy who completed the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment. Salivary microbiome composition was determined using 16S rRNA amplicon sequencing. Results: There was no significant correlation between alpha diversity and primary measures of short-term dietary intake (total daily calories, fat, fiber, fruit/vegetables, red meat intake, and fasting time). There was no evidence of clustering on beta diversity analyses. Very few taxonomic alterations were found for short-term dietary intake; an increased relative abundance of Neisseria oralis and Lautropia sp. was associated with high fruit and vegetable intake, and an increased relative abundance of a taxon in the family Gemellaceae was associated with increased red meat intake. Conclusions: Short-term dietary intake was associated with only minimal salivary microbiome alterations and does not appear to have a major impact on the potential use of the salivary microbiome as a biomarker for esophageal neoplasia.

Resilience of the oral microbiome

The human mouth harbors a complex microbiota, the composition of which is potentially influenced by a wide range of factors, including the intake of food and drink, the availability of endogenous nutrients, the host immune system, drug treatments, and systemic diseases. Despite these possible influences, the oral microbiota is remarkably resilient, particularly in comparison with the microbiota of the large intestine. Diet, with the exception of excessive and/or frequent consumption of fermentable carbohydrate or supplementation with nitrate, has minimal impact on the composition of the oral bacterial community. The common oral diseases dental caries and the periodontal diseases is associated with modification of the oral microbiota primarily as a result of the ecological changes induced by excessive acid production and inflammation, respectively. Systemically-administered antimicrobials have only a small effect on the composition of the oral bacterial community, and while locally delivered antimicrobials can have some clinical benefits, the biofilm lifestyle of oral bacteria lends them substantial resistance to the agents used. Saliva plays an important role in oral microbial ecology, by supplying nutrients and providing protection against colonization by nonoral organisms. Dry mouth is one condition that has a major effect on the microbiota, resulting in increased colonization by opportunistic pathogens. Some systemic diseases do affect the oral microbiome, notably diabetes, in which raised levels of glucose in saliva and tissue impact on bacterial nutrition.

Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load

Evaluating microbial community composition through next-generation sequencing has become increasingly accessible. However, metagenomic sequencing data sets provide researchers with only a snapshot of a dynamic ecosystem and do not provide information about the total microbial number, or load, of a sample. Additionally, DNA can be detected long after a microorganism is dead, making it unsafe to assume that all microbial sequences detected in a community came from living organisms. By combining relic DNA removal by propidium monoazide (PMA) with microbial quantification with flow cytometry, we present a novel workflow to quantify live microbial load in parallel with metagenomic sequencing. We applied this method to unstimulated saliva samples, which can easily be collected longitudinally and standardized by passive collection time. We found that the number of live microorganisms detected in saliva was inversely correlated with salivary flow rate and fluctuated by an order of magnitude throughout the day in healthy individuals. In an acute perturbation experiment, alcohol-free mouthwash resulted in a massive decrease in live bacteria, which would have been missed if we did not consider dead cell signal. While removing relic DNA from saliva samples did not greatly impact the microbial composition, it did increase our resolution among samples collected over time. These results provide novel insight into the dynamic nature of host-associated microbiomes and underline the importance of applying scale-invariant tools in the analysis of next-generation sequencing data sets.

IMPORTANCE Human microbiomes are dynamic ecosystems often composed of hundreds of unique microbial taxa. To detect fluctuations over time in the human oral microbiome, we developed a novel workflow to quantify live microbial cells with flow cytometry in parallel with next-generation sequencing, and applied this method to over 150 unstimulated, timed saliva samples. Microbial load was inversely correlated with salivary flow rate and fluctuated by an order of magnitude within a single participant throughout the day. Removing relic DNA improved our ability to distinguish samples over time and revealed that the percentage of sequenced bacteria in a given saliva sample that are alive can range from nearly 0% up to 100% throughout a typical day. These findings highlight the dynamic ecosystem of the human oral microbiome and the benefit of removing relic DNA signals in longitudinal microbiome study designs.

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.

Salivary microbiome composition changes after bariatric surgery

Recent studies show that the salivary microbiome in subjects with obesity differ from those without obesity, but the mechanism of interaction between the salivary microbiome composition and body weight is unclear. Herein we investigate this relation by analyzing saliva samples from 35 adult patients with obesity undergoing bariatric surgery. Our aim was to describe salivary microbiome changes during body weight loss on an individual-specific level, and to elucidate the effect of bariatric surgery on the salivary microbiome which has not been studied before. Analysis of samples collected before and 1 day after surgery, as well as 3 and 12 months after surgery, showed that the salivary microbiome changed in all study participants, but these changes were heterogeneous. In the majority of participants proportions of Gemella species, Granulicatella elegans, Porphyromonas pasteri, Prevotella nanceiensis and Streptococcus oralis decreased, while Veillonella species, Megasphaera micronuciformis and Prevotella saliva increased. Nevertheless, we found participants deviating from this general trend which suggests that a variety of individual-specific factors influence the salivary microbiome composition more effectively than the body weight dynamics alone. The observed microbiome alternations could be related to dietary changes. Therefore, further studies should focus on association with altered taste preferences and potential oral health consequences.

Impact of Diabetes on the Gut and Salivary IgA Microbiomes

Mucosal surfaces like those present in the lung, gut, and mouth interface with distinct external environments. These mucosal gateways are not only portals of entry for potential pathogens but also homes to microbial communities that impact host health. Secretory immunoglobulin A (SIgA) is the single most abundant acquired immune component secreted onto mucosal surfaces and, via the process of immune exclusion, shapes the architecture of these microbiomes. Not all microorganisms at mucosal surfaces are targeted by SIgA; therefore, a better understanding of the SIgA-coated fraction may identify the microbial constituents that stimulate host immune responses in the context of health and disease. Chronic diseases like type 2 diabetes are associated with altered microbial communities (dysbiosis) that in turn affect immune-mediated homeostasis. 16S rRNA gene sequencing of SIgA-coated/uncoated bacteria (IgA-Biome) was conducted on stool and saliva samples of normoglycemic participants and individuals with prediabetes or diabetes (n = 8/group). These analyses demonstrated shifts in relative abundance in the IgA-Biome profiles between normoglycemic, prediabetic, or diabetic samples distinct from that of the overall microbiome. Differences in IgA-Biome alpha diversity were apparent for both stool and saliva, while overarching bacterial community differences (beta diversity) were also observed in saliva. These data suggest that IgA-Biome analyses can be used to identify novel microbial signatures associated with diabetes and support the need for further studies exploring these communities. Ultimately, an understanding of the IgA-Biome may promote the development of novel strategies to restructure the microbiome as a means of preventing or treating diseases associated with dysbiosis at mucosal surfaces.

Influence of the long-term use of oral hygiene products containing stannous ions on the salivary microbiome - a randomized controlled trial

Oral hygiene products containing tin are suitable to prevent erosive tooth wear, yet effects on the oral microbiota are not known yet. Therefore, this study determined the salivary microbiome of 16 participants using products with stannous ions for three years (TG) compared with a control group (CG) to assess their influence on the microbiota. Participants were included in a randomized controlled clinical trial (RCT) with biannual visits. Illumina Miseq sequencing revealed as most abundant genera: Streptococcus (TG 14.3%; CG 13.0%), Veillonella (TG 11.3%; CG 10.9%), Prevotella (TG 7.0%; CG 9.8%), Haemophilus (TG 6.6%; CG 7.2%), Porphyromonas (TG 5.9%, CG 5.1%), Leptotrichia (TG 5.8%; CG 4.9%), Actinomyces (TG 4.0%; CG 4.6%) and Neisseria (TG 5.4%; CG 4.2%). Beta-Diversity was not significantly different between groups at both time points, although significant differences between groups were found for certain taxa after three years. The genus Prevotella was found in higher abundance in CG whereas Neisseria and Granulicatella, health-associated taxa, were found more abundantly in TG. Salivary microbiota after three years reflected a composition associated with oral health, hence continual use as a preventive measure for dental erosion can be considered safe and benefitting oral health for patients with a high risk of erosion.

Optimizing 16S rRNA gene profile analysis from low biomass nasopharyngeal and induced sputum specimens

BACKGROUND

Careful consideration of experimental artefacts is required in order to successfully apply high-throughput 16S ribosomal ribonucleic acid (rRNA) gene sequencing technology. Here we introduce experimental design, quality control and "denoising" approaches for sequencing low biomass specimens.

RESULTS

We found that bacterial biomass is a key driver of 16S rRNA gene sequencing profiles generated from bacterial mock communities and that the use of different deoxyribonucleic acid (DNA) extraction methods [DSP Virus/Pathogen Mini Kit® (Kit-QS) and ZymoBIOMICS DNA Miniprep Kit (Kit-ZB)] and storage buffers [PrimeStore® Molecular Transport medium (Primestore) and Skim-milk, Tryptone, Glucose and Glycerol (STGG)] further influence these profiles. Kit-QS better represented hard-to-lyse bacteria from bacterial mock communities compared to Kit-ZB. Primestore storage buffer yielded lower levels of background operational taxonomic units (OTUs) from low biomass bacterial mock community controls compared to STGG. In addition to bacterial mock community controls, we used technical repeats (nasopharyngeal and induced sputum processed in duplicate, triplicate or quadruplicate) to further evaluate the effect of specimen biomass and participant age at specimen collection on resultant sequencing profiles. We observed a positive correlation (r = 0.16) between specimen biomass and participant age at specimen collection: low biomass technical repeats (represented by < 500 16S rRNA gene copies/μl) were primarily collected at < 14 days of age. We found that low biomass technical repeats also produced higher alpha diversities (r = - 0.28); 16S rRNA gene profiles similar to no template controls (Primestore); and reduced sequencing reproducibility. Finally, we show that the use of statistical tools for in silico contaminant identification, as implemented through the decontam package in R, provides better representations of indigenous bacteria following decontamination.

CONCLUSIONS

We provide insight into experimental design, quality control steps and "denoising" approaches for 16S rRNA gene high-throughput sequencing of low biomass specimens. We highlight the need for careful assessment of DNA extraction methods and storage buffers; sequence quality and reproducibility; and in silico identification of contaminant profiles in order to avoid spurious results.

Mechanism of Candida pathogenesis: revisiting the vital drivers

Candida is the most implicated fungal pathogen in the clinical setting. Several factors play important roles in the pathogenesis of Candida spp. Multiple transcriptional circuits, morphological and phenotypic switching, biofilm formation, tissue damaging extracellular hydrolytic enzymes, metabolic flexibility, genome plasticity, adaptation to environmental pH fluctuation, robust nutrient acquisition system, adherence and invasions (mediated by adhesins and invasins), heat shock proteins (HSPs), cytolytic proteins, escape from phagocytosis, evasion from host immune system, synergistic coaggregation with resident microbiota, resistance to antifungal agents, and the ability to efficiently respond to multiple stresses are some of the major pathogenic determinants of Candida species. The existence of multiple connections, in addition to the interactions and associations among all of these factors, are distinctive features that play important roles in the establishment of Candida infections. This review describes all the underlying factors and mechanisms involved in Candida pathogenesis by evaluating pathogenic determinants of Candida species. It reinforces the already available pool of data on the pathogenesis of Candida species by providing a clear and simplified understanding of the most important factors implicated in the pathogenesis of Candida species. The Candida pathogenesis network, an illustration linking all the major determinants of Candida pathogenesis, is also presented. Taken together, they will further improve our current understanding of how these factors modulate virulence and consequent infection(s). Development of new antifungal drugs and better therapeutic approaches to candidiasis can be achieved in the near future with continuing progress in the understanding of the mechanisms of Candida pathogenesis.

Profiling of Oral Bacterial Communities

The profiling of bacterial communities by the sequencing of housekeeping genes such as that encoding the small subunit ribosomal RNA has revealed the extensive diversity of bacterial life on earth. Standard protocols have been developed and are widely used for this application, but individual habitats may require modification of methods. This review discusses the sequencing and analysis methods most appropriate for the study of the bacterial component of the human oral microbiota. If possible, DNA should be extracted from samples soon after collection. If samples have to be stored for practical reasons, precautions to avoid DNA degradation on freezing should be taken. A critical aspect of profiling oral bacterial communities is the choice of region of the 16S rRNA gene for sequencing. The V1-V2 region provides the best discrimination between species of the genus Streptococcus, the most common genus in the mouth and important in health and disease. The MiSeq platform is most commonly used for sequencing, but long-read technologies are now becoming available that should improve the resolution of analyses. There are a variety of well-established data analysis pipelines available, including mothur and QIIME, which identify sequence reads as phylotypes by comparing them to reference data sets or grouping them into operational taxonomic units. DADA2 has improved sequence error correction capabilities and resolves reads to unique variants. Two curated oral 16S rRNA databases are available: HOMD and CORE. Expert interpretation of community profiles is required, both to detect the presence of contaminating DNA, which is commonly present in the reagents used in analysis, and to differentiate oral and nonoral bacteria and determine the significance of findings. Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling via 16S rRNA sequence analysis remains a valuable technique for the characterization of oral bacterial populations.

Profiling the Salivary microbiome of the Qatari population

BACKGROUND

The role of the human microbiome in human health and disease has been studied in various body sites. However, compared to the gut microbiome, where most of the research focus is, the salivary microbiome still bears a vast amount of information that needs to be revealed. This study aims to characterize the salivary microbiome composition in the Qatari population, and to explore specific microbial signatures that can be associated with various lifestyles and different oral conditions.

MATERIALS AND METHODS

We characterized the salivary microbiome of 997 Qatari adults using high-throughput sequencing of the V1-V3 region of the 16S rRNA gene.

RESULTS

In this study, we have characterized the salivary microbiome of 997 Qatari participants. Our data show that Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria are the common phyla isolated from the saliva samples, with Bacteroidetes being the most predominant phylum. Bacteroidetes was also more predominant in males versus females in the study cohort, although differences in the microbial diversity were not statistically significant. We also show that, a lower diversity of the salivary microbiome is observed in the elderly participants, with Prevotella and Treponema being the most significant genera. In participants with oral conditions such as mouth ulcers, bleeding or painful gum, our data show that Prevotella and Capnocytophaga are the most dominant genera as compared to the controls. Similar patterns were observed in participants with various smoking habits as compared to the non-smoking participants. Our data show that Streptococcus and Neisseria are more dominant among denture users, as compared to the non-denture users. Our data also show that, abnormal oral conditions are associated with a reduced microbial diversity and microbial richness. Moreover, in this study we show that frequent coffee drinkers have higher microbial diversity compared to the non-drinkers, indicating that coffee may cause changes to the salivary microbiome. Furthermore, tea drinkers show higher microbial richness as compared to the non-tea drinkers.

CONCLUSION

This is the first study to assess the salivary microbiome in an Arab population, and one of the largest population-based studies aiming to the characterize the salivary microbiome composition and its association with age, oral health, denture use, smoking and coffee-tea consumption.

Microbial Metabolism Modulates Antibiotic Susceptibility within the Murine Gut Microbiome

Although antibiotics disturb the structure of the gut microbiota, factors that modulate these perturbations are poorly understood. Bacterial metabolism is an important regulator of susceptibility in vitro and likely plays a large role within the host. We applied a metagenomic and metatranscriptomic approach to link antibiotic-induced taxonomic and transcriptional responses within the murine microbiome. We found that antibiotics significantly alter the expression of key metabolic pathways at the whole-community and single-species levels. Notably, Bacteroides thetaiotaomicron, which blooms in response to amoxicillin, upregulated polysaccharide utilization. In vitro, we found that the sensitivity of this bacterium to amoxicillin was elevated by glucose and reduced by polysaccharides. Accordingly, we observed that dietary composition affected the abundance and expansion of B. thetaiotaomicron, as well as the extent of microbiome disruption with amoxicillin. Our work indicates that the metabolic environment of the microbiome plays a role in the response of this community to antibiotics.

Gender-Specific Associations Between Saliva Microbiota and Body Size

Objective

The human intestinal microbiota likely play an important role in the development of overweight and obesity. However, the associations between saliva microbiota and body mass index (BMI) have been sparsely studied. The aim of this study was to identify the associations between saliva microbiota and body size in Finnish children.

Methods

The saliva microbiota of 900 Finnish children, aged 11–14 years with measured height and weight, was characterized using 16S rRNA (V3–V4) sequencing.

Results

The core saliva microbiota consisted of 14 genera that were present in more than 95% of the Finnish children. The saliva microbiota profiles were gender-specific with higher alpha-diversity in boys than girls and significant differences between the genders in community composition and abundances. Alpha-diversity differed between normal weight and overweight girls and between normal weight and obese boys. The composition was dissimilar between normal weight and obese girls, but not in boys. The relative abundance profiles differed according to body size. Decrease in commensal saliva bacteria were observed in all the body sizes when compared to normal weight children. Notably, the relative abundance of bacteria related to, Veillonella, Prevotella, Selenomonas, and Streptococcus was reduced in obese children.

Conclusion

Saliva microbiota diversity and composition were significantly associated with body size and gender in Finnish children. Body size–specific saliva microbiota profiles open new avenues for studying the potential roles of microbiota in weight development and management.

In-vivo shift of the microbiota in oral biofilm in response to frequent sucrose consumption

Caries is associated with shifts of microbiota in dental biofilms and primarily driven by frequent sucrose consumption. Data on environmentally induced in vivo microbiota shifts are scarce therefore we investigated the influence of frequent sucrose consumption on the oral biofilm. Splint systems containing enamel slabs were worn for 3 × 7 days with 7-day intervals to obtain oral biofilm samples. After a three-month dietary change of sucking 10 g of sucrose per day in addition to the regular diet, biofilm was obtained again at the end of the second phase. The microbiota was analysed using Illumina MiSeq amplicon sequencing (v1-v2 region). In addition, roughness of the enamel surface was measured with laser scanning microscopy. The sucrose phase resulted in significant differences in beta-diversity and significantly decreased species richness. It was marked by a significant increase in abundance of streptococci, specifically Streptococcus gordonii, Streptococcus parasanguinis and Streptococcus sanguinis. Enamel surface roughness began to increase, reflecting initial impairment of dental enamel surface. The results showed that frequent sucrose consumption provoked compositional changes in the microbiota, leading to an increase of non-mutans streptococci, hence supporting the extended ecological plaque hypothesis and emphasizing the synergy of multiple bacterial species in the development of caries.

High-resolution ISR amplicon sequencing reveals personalized oral microbiome

BACKGROUND

Sequencing of the 16S rRNA gene has been the standard for studying the composition of microbial communities. While it allows identification of bacteria at the level of species, this method does not usually provide sufficient information to resolve communities at the sub-species level. Species-level resolution is not adequate for studies of transmission or stability or for exploring subspecies variation in disease association. Strain level analysis using whole metagenome shotgun sequencing has significant limitations that can make it unsuitable for large-scale studies. Achieving sufficient depth of sequencing can be cost-prohibitive, and even with adequate coverage, deconvoluting complex communities such as the oral microbiota is computationally very challenging. Thus, there is a need for high-resolution, yet cost-effective, high-throughput methods for characterizing microbial communities.

RESULTS

Significant improvement in resolution for amplicon-based bacterial community analysis was achieved by combining amplicon sequencing of a high-diversity marker gene, the ribosomal 16-23S intergenic spacer region (ISR), with a probabilistic error modeling based denoising algorithm, DADA2. The resolving power of this new approach was compared to that of both standard and high-resolution 16S-based approaches using a set of longitudinal subgingival plaque samples. The ISR strategy resulted in a 5.2-fold increase in community resolution compared to reference-based 16S rRNA gene analysis and showed 100% accuracy in predicting the correct source of a clinical sample. Individuals' microbial communities were highly personalized, and although they exhibited some drift in membership and levels over time, that difference was always smaller than the differences between any two subjects, even after 1 year. The construction of an ISR database from publicly available genomic sequences allowed us to explore genomic variation within species, resulting in the identification of multiple variants of the ISR for most species.

CONCLUSIONS

The ISR approach resulted in significantly improved resolution of communities and revealed a highly personalized human oral microbiota that was stable over 1 year. Multiple ISR types were observed for all species examined, demonstrating a high level of subspecies variation in the oral microbiota. The approach is high-throughput, high-resolution yet cost-effective, allowing subspecies-level community fingerprinting at a cost comparable to that of 16S rRNA gene amplicon sequencing. It will be useful for a range of applications that require high-resolution identification of organisms, including microbial tracking, community fingerprinting, and potentially for identification of virulence-associated strains.

Microbial Community Analysis of Sauerkraut Fermentation Reveals a Stable and Rapidly Established Community

Despite recent interest in microbial communities of fermented foods, there has been little inquiry into the bacterial community dynamics of sauerkraut, one of the world’s oldest and most prevalent fermented foods. In this study, we utilize 16S rRNA amplicon sequencing to profile the microbial community of naturally fermented sauerkraut throughout the fermentation process while also analyzing the bacterial communities of the starting ingredients and the production environment. Our results indicate that the sauerkraut microbiome is rapidly established after fermentation begins and that the community is stable through fermentation and packaging for commercial sale. Our high-throughput analysis is in agreement with previous studies that utilized traditional microbiological assessments but expands the identified taxonomy. Additionally, we find that the microbial communities of the starting ingredients and the production facility environment exhibit low relative abundance of the lactic acid bacteria that dominate fermented sauerkraut.

Microbial competition between Escherichia coli and Candida albicans reveals a soluble fungicidal factor

Localized and systemic fungal infections caused by Candida albicans can lead to significant mortality and morbidity. However, severe C. albicans infections are relatively rare, occurring mostly in the very young, the very old, and immunocompromised individuals. The fact that these infections are rare is interesting because as much as 80 percent of the population is asymptomatically colonized with C. albicans. It is thought that members of the human microbiota and the immune system work in concert to reduce C. albicans overgrowth through competition and modification of the growth environment. Here, we report that Escherichia coli (strain MG1655) outcompetes and kills C. albicans (strain SC5314) in vitro. We find that E. coli produces a soluble factor that kills C. albicans in a magnesium-dependent fashion such that depletion of available magnesium is essential for toxicity.

Antibiotic Persistence as a Metabolic Adaptation: Stress, Metabolism, the Host, and New Directions

Persistence is a phenomenon during which a small fraction of a total bacterial population survives treatment with high concentrations of antibiotics for an extended period of time. In conjunction with biofilms, antibiotic persisters represent a major cause of recalcitrant and recurring infections, resulting in significant morbidity and mortality. In this review, we discuss the clinical significance of persister cells and the central role of bacterial metabolism in their formation, specifically with respect to carbon catabolite repression, sugar metabolism, and growth regulation. Additionally, we will examine persister formation as an evolutionary strategy used to tolerate extended periods of stress and discuss some of the response mechanisms implicated in their formation. To date, the vast majority of the mechanistic research examining persistence has been conducted in artificial in vitro environments that are unlikely to be representative of host conditions. Throughout this review, we contextualize the existing body of literature by discussing how in vivo conditions may create ecological niches that facilitate the development of persistence. Lastly, we identify how the development of next-generation sequencing and other “big data” tools may enable researchers to examine persistence mechanisms within the host to expand our understanding of their clinical importance.