Microbiota and Metatranscriptome Changes Accompanying the Onset of Gingivitis

Supragingival microbiota, cytokines, and proteins in individuals with different trajectories in experimental gingivitis

Background

Gingivitis in response to biofilm formation may exhibit different trajectories. The purposes of the present study were to characterize the composition of the supragingival microbiota and salivary cytokine and protein levels in healthy individuals with different gingivitis patterns, to test the hypothesis that manifestations of gingivitis associate with specific profiles in terms of supragingival microbiota, salivary cytokines, and proteins.

Methods

Forty orally and systemically healthy individuals refrained from all oral hygiene procedures for a period of 14 days, followed by a resolution period of 14 days with regular oral care. Supragingival plaque level and bleeding on probing (BOP) were recorded, and supragingival plaque as well as saliva samples were collected at baseline, day 14, and day 28. Based on change in BOP% from baseline to day 14, rapid (n = 15), moderate (n = 10), and slow (n = 15) responders were identified. Supragingival microbiota composition, salivary cytokine, and protein levels were compared between groups at baseline, day 14, and day 28.

Results

A significantly higher baseline abundance of Capnocytophaga, Eikenella, and Campylobacter species were recorded in rapid responders, whereas a significantly higher baseline abundance of Streptococcus species were detected in slow responders. Slow responders expressed a high degree of resilience, with minimal difference in microbial composition at baseline and after 14 days of resolution (day 28). On the contrary, significant differences in relative abundance of members of the core microbiota, Streptococcus, Actinomyces, and Rothia species, was noted in baseline samples versus day 28 samples in rapid responders. Comparable baseline cytokine and protein levels were recorded in all groups.

Conclusion

Supragingival microbiota composition, but not saliva cytokine and protein profiles, seems to influence the extent of the inflammatory response during development of gingivitis in systemically healthy individuals.

Effects of toothpaste containing inactivated Lacticaseibacillus paracasei Probio-01 on plaque-induced gingivitis and dental plaque microbiota

Plaque-induced gingivitis is an inflammatory response in gingival tissues resulting from bacterial plaque accumulation at the gingival margin. Postbiotics can promote the proliferation of beneficial bacteria and optimise the state of microbiota in the oral cavity. In this study, we investigated the effect of inactivated Lacticaseibacillus paracasei Probio-01 on plaque-induced gingivitis and the dental plaque microbiota. A total of 32 healthy gingival participants (Group N, using blank toothpaste for 3 months) and 60 patients with plaque-induced gingivitis (30 in Group F, using inactivated Probio-01 toothpaste for 3 months, and 30 in Group B, using blank toothpaste for 3 months, respectively) were recruited. Clinical indices, which included bleeding on probing (BOP), gingival index (GI), and plaque index (PI), were used to assess the severity of gingivitis. Furthermore, 16SrDNA amplicon sequencing was used to explore changes in the gingival state and dental plaque microbiota in patients with plaque-induced gingivitis. The results showed that inactivated Probio-01 significantly reduced clinical indices of gingivitis, including BOP, GI, and PI, in participants with plaque-induced gingivitis and effectively relieved gingival inflammation, compared with that observed in the control group (group B). Inactivated Probio-01 did not significantly influence the diversity of dental plaque microbiota, but increased the relative abundance of dental plaque core bacteria, such as Leptotrichia and Fusobacterium (P < 0.05). Strong correlations were observed between the indices and abundance of dental plaque microbiota. Overall, the inactivated Probio-01 significantly reduced the clinical indices of gingivitis and effectively improved gingival inflammation in patients with plaque-induced gingivitis. The activity of inactivated Probio-01 against plaque-induced gingivitis was possibly mediated by its ability to regulate the dental plaque microbiota, as indicated by the close correlation between the plaque microbiota and clinical indices of gingivitis.

Supra- and Subgingival Microbiome in Gingivitis and Impact of Biofilm Control: A Comprehensive Review

This comprehensive review aimed (1) to characterize the sub- and supragingival microbiome in patients with biofilm-induced gingivitis (including experimental gingivitis), (2) to assess its stability and evolution over time, and (3) to assess the impact of biofilm control measures on this stability. An electronic search of the MEDLINE®/PubMed® database until December 2023 was conducted. NCBI Taxonomy, eHOMD 16S rRNA Reference Sequence, and Tree Version 15.23 databases were used to standardize taxonomic nomenclature. Out of 89 papers initially retrieved, 14 studies were finally included: 11 using experimental gingivitis as a model and three randomized clinical trials evaluating the impact of biofilm control measures. Among them, five characterized the subgingival microbiome, nine the supragingival microbiome, and one both the sub- and supragingival microbiome. In addition, five studies evaluated the effect of toothpaste, and four studies evaluated the effect of mouth rinses. The diversity and structure of the microbiome differed significantly between patients with periodontal health and those with biofilm-induced gingivitis (including experimental gingivitis). Those differences were not reversed through conventional oral hygiene measures. Specific antiseptic agents, especially if delivered as mouth rinses, may have an impact on the supra- and subgingival microbiome in gingivitis.

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.

Effect of Probiotic Supplements on the Oral Microbiota-A Narrative Review

Data from systematic reviews and meta-analyses show that probiotics positively impact clinical parameters of oral diseases such as gingivitis, dental caries, and periodontitis. However, the working mechanism of probiotics is not fully understood, but is hypothesized to be mediated by direct and indirect interactions with the oral microbiota and the human host. In the present narrative review, we focused on the microbiological effect of probiotic supplements based on data retrieved from randomized clinical trials (RCTs). In addition, we assessed to what extent contemporary molecular methods have been employed in clinical trials in the field of oral probiotics. Multiple RCTs have been performed studying the potential effect of probiotics on gingivitis, dental caries, and periodontitis, as evaluated by microbial endpoints. In general, results are conflicting, with some studies reporting a positive effect, whereas others are not able to record any effect. Major differences in terms of study designs and sample size, as well as delivery route, frequency, and duration of probiotic consumption, hamper comparison across studies. In addition, most RCTs have been performed with a limited sample size using relatively simple methods for microbial identification, such as culturing, qPCR, and DNA-DNA checkerboard, while high-throughput methods such as 16S sequencing have only been employed in a few studies. Currently, state-of-the-art molecular methods such as metagenomics, metatranscriptomics, and metaproteomics have not yet been used in RCTs in the field of probiotics. The present narrative review revealed that the effect of probiotic supplements on the oral microbiota remains largely uncovered. One important reason is that most RCTs are performed without studying the microbiological effect. To facilitate future systematic reviews and meta-analyses, an internationally agreed core outcome set for the reporting of microbial endpoints in clinical trials would be desirable. Such a standardized collection of outcomes would most likely improve the quality of probiotic research in the oral context.

Microbiota Transplantation as an Adjunct to Standard Periodontal Treatment in Periodontal Disease: A Systematic Review

Periodontitis is a disease linked to severe dysbiosis of the subgingival microbiome. The treatment of periodontitis aims to change the dysbiosis environment to a symbiosis environment. We hypothesized that oral microbiota transplantation can lead to a significant improvement in periodontitis. Therefore, the aim of this study was to determine the effectiveness of microbiota transplantation after standard periodontal treatment in periodontitis patients. The search strategy was carried out by using the Boolean term "AND" to combine the keywords, which were "periodontitis AND microbiota transplantation". Due to the limited resources of the study, we included both in vitro and in vivo investigations in this systematic review. The QUIN risk of bias tool was employed to assess the risk of bias in in vitro studies, while SYRCLE's risk of bias assessment was used for in vivo studies. Oral microbiota transplants (OMTs) have shown potential in treating periodontitis. OMTs significantly reduced periodontitis-associated pathogenic microbial species (P. endodontalis, Prevotella intermedia, T. vincentii, Porphyromonas sp.) and increased beneficial bacteria (P. melaninogenica, Fusobacterium nucleatum, P. catoniae, Capnocytophaga ochracea, C. sputigena, C. gingivalis, Haemophilus parainfluenzae, and Neisseria elongata) upon in vitro testing. Furthermore, in the in vivo tests, single adjunctive OMT also had an effect on the oral microbiota composition compared to the full-mouth mechanical and antimicrobial debridement. OMTs may be cheaper and more effective at addressing high-risk individuals. At present, it is not possible to provide OMT clinical advice due to the lack of available information. This treatment needs to be subjected to more safety and efficacy testing before being included human clinical trials.

Shotgun metagenomic analysis of the oral microbiome in gingivitis: a nested case-control study

Background

Gingivitis, i.e. inflammation of the gums, is often induced by dentalplaque. However, its exact link to the oral microbiota remains unclear.

Methods

In a case-control study involving 120 participants, comprising 60 cases and 60 controls (mean age (SD) 36.6 (7.6) years; 50% males), nested within a prospective multicentre cohort study, we examined theoral microbiome composition of gingivitis patients and their controlsusing shotgun metagenomic sequencing of saliva samples. Participants underwent clinical and radiographic oral health examinations, including bleeding on probing (BOP), at six tooth sites. BOP ≥33%was considered 'generalized gingivitis/initial periodontitis'(GG/IP), and BOP <33% as 'healthy and localized gingivitis'(H/LG). Functional potential was inferred using HUMANn3.

Results

GG/IP exhibited an increase in the abundance of Actinomyces, Porphyromonas, Aggregatibacter, Corynebacterium, Olsenella, and Treponema, whereas H/LG exhibited an increased abundance of Candidatus Nanosynbacter. Nineteen bacterial species and fourmicrobial functional profiles, including L-methionine, glycogen, andinosine-5'-phosphate biosynthesis, were associated with GG/IP. Constructing models with multiple markers resulted in a strong predictive value for GG/IP, with an area under the curve (ROC) of 0.907 (95% CI: 0.848-0.966).

Conclusion

We observed distinct differences in the oral microbiome between the GG/IP and H/LG groups, indicating similar yet unique microbial profiles and emphasizing their potential role in progression of periodontal diseases.

A novel method for sampling subgingival microbiome: a comparative metatranscriptomic study

The subgingival microbiome has been implicated in oral and systemic diseases such as periodontitis and Alzheimer's disease. However, subgingival sampling is challenging. We developed a novel method of sampling the subgingival microbiome by rotationally swabbing the supragingival area, named subgingival-P (for proxy) samples. We sampled and metatranscriptomically analyzed subgingival and subgingival-P samples of three different teeth in 20 individuals. The subgingival-P samples were comparable to the subgingival samples in the relative abundances of microorganisms and microbial gene expression levels. Our data demonstrate that the novel method of collecting and analyzing the subgingival-P samples can act as a proxy for the subgingiva, paving the way for large and diverse studies investigating the role of the subgingival microbiome in health and disease.

Oral microbiome associated with differential ratios of Porphyromonas gingivalis and Streptococcus cristatus

Periodontitis has recently been defined as a dysbiotic disease caused by an imbalanced oral microbiota. The transition from commensal microbial communities to periodontitis-associated ones requires colonization by specific pathogens, including Porphyromonas gingivalis. We previously reported an antagonistic relationship between Streptococcus cristatus and P. gingivalis. To determine the role of S. cristatus in altering the interactions of P. gingivalis with other oral bacteria in a complex context, we collected dental plaque samples from patients with periodontitis and assigned them to two groups based on the ratios of S. cristatus and P. gingivalis. We then characterized the microbial profiles of the dental plaque samples using shotgun metagenomic sequencing and compared the oral microbial composition and functional capabilities of the group with high S. cristatus-P. gingivalis ratios with the low ratio group. Taxonomic annotation revealed significant differences in the microbial composition at both the genus and species levels between the low and high S. cristatus-P. gingivalis ratio groups. Notably, a higher microbial diversity was observed in the samples with low S. cristatus-P. gingivalis ratios. Furthermore, the antibiotic resistance gene profiles of the two groups were also distinct, with a significantly increased abundance of the genes in the dental plaque samples with low S. cristatus-P. gingivalis ratios. It, therefore, indicates that the S. cristatus-P. gingivalis ratios influenced the virulence potential of the oral microbiome. Our work shows that enhancing the S. cristatus-P. gingivalis ratio in oral microbial communities can be an attractive approach for revising the dysbiotic oral microbiome.IMPORTANCEPeriodontitis, one of the most common chronic diseases, is linked to several systemic diseases, such as cardiovascular disease and diabetes. Although Porphyromonas gingivalis is a keystone pathogen that causes periodontitis, its levels, interactions with accessory bacteria and pathobionts in the oral microbiome, and its association with the pathogenic potential of the microbial communities are still not well understood. In this study, we revealed the role of Streptococcus cristatus and the ratios of S. cristatus and P. gingivalis in modulating the oral microbiome to facilitate a deeper understanding of periodontitis and its progression. The study has important clinical implications as it laid a foundation for developing novel non-antibiotic therapies against P. gingivalis and improving the efficiency of periodontal treatments.

Omics for deciphering oral microecology

The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.

A distinctive subgingival microbiome in patients with periodontitis and Alzheimer's disease compared with cognitively unimpaired periodontitis patients

AIM

Periodontitis is caused by dysbiosis of oral microbes and is associated with increased cognitive decline in Alzheimer's disease (AD), and recently, a potential functional link was proposed between oral microbes and AD. We compared the oral microbiomes of patients with or without AD to evaluate the association between oral microbes and AD in periodontitis.

MATERIALS AND METHODS

Periodontitis patients with AD (n = 15) and cognitively unimpaired periodontitis patients (CU) (n = 14) were recruited for this study. Each patient underwent an oral examination and neuropsychological evaluation. Buccal, supragingival and subgingival plaque samples were collected, and microbiomes were analysed by next-generation sequencing. Alpha diversity, beta diversity, linear discriminant analysis effect size, analysis of variance-like differential expression analysis and network analysis were used to compare group oral microbiomes.

RESULTS

All 29 participants had moderate to severe periodontitis. Group buccal and supragingival samples were indistinguishable, but subgingival samples demonstrated significant alpha and beta diversity differences. Differential analysis showed subgingival samples of the AD group had higher prevalence of Atopobium rimae, Dialister pneumosintes, Olsenella sp. HMT 807, Saccharibacteria (TM7) sp. HMT 348 and several species of Prevotella than the CU group. Furthermore, subgingival microbiome network analysis revealed a distinct, closely connected network in the AD group comprised of various Prevotella spp. and several anaerobic bacteria.

CONCLUSIONS

A unique microbial composition was discovered in the subgingival region in the AD group. Specifically, potential periodontal pathogens were found to be more prevalent in the subgingival plaque samples of the AD group. These bacteria may possess a potential to worsen periodontitis and other systemic diseases. We recommend that AD patients receive regular, careful dental check-ups to ensure proper oral hygiene management.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

The increasing importance of the oral microbiome in periodontal health and disease

Herein, the aim is to discuss the current knowledge of microbiome and periodontal diseases. Current treatment strategies include mechanical therapy such as root planing, scaling, deep pocket debridement and antimicrobial chemotherapy as an adjuvant therapy. Among promising therapeutic strategies, dental probiotics and oral microbiome transplantation have gained attention, and may be used to treat bacterial imbalances by competing with pathogenic bacteria for nutrients and adhesion surfaces, as well as probiotics targeting the gut microbiome. Development of strategies to prevent and treat periodontal diseases are warranted as both are highly prevalent and can affect human health. Further studies are necessary to better comprehend the microbiome in order to develop innovative preventative measures as well as efficacious therapies against periodontal diseases.

Periodontal Pathogens and Their Links to Neuroinflammation and Neurodegeneration

Pathogens that play a role in the development and progression of periodontitis have gained significant attention due to their implications in the onset of various systemic diseases. Periodontitis is characterized as an inflammatory disease of the gingival tissue that is mainly caused by bacterial pathogens. Among them, Porphyromonas gingivalis, Treponema denticola, Fusobacterium nucleatum, Aggregatibacter actinomycetemcomitans, and Tannerella forsythia are regarded as the main periodontal pathogens. These pathogens elicit the release of cytokines, which in combination with their virulence factors induce chronic systemic inflammation and subsequently impact neural function while also altering the permeability of the blood-brain barrier. The primary objective of this review is to summarize the existing information regarding periodontal pathogens, their virulence factors, and their potential association with neuroinflammation and neurodegenerative diseases. We systematically reviewed longitudinal studies that investigated the association between periodontal disease and the onset of neurodegenerative disorders. Out of the 24 studies examined, 20 showed some degree of positive correlation between periodontal disease and neurodegenerative disorders, with studies focusing on cognitive function demonstrating the most robust effects. Therefore, periodontal pathogens might represent an exciting new approach to develop novel preventive treatments for neurodegenerative diseases.

Subgingival microbiome in periodontal health, gingivitis and different stages of periodontitis

AIM

To characterize the subgingival microbiome in subjects with different periodontal health statuses.

MATERIALS AND METHODS

In this cross-sectional observational study, subgingival samples were harvested from Spanish subjects with different periodontal health statuses, based on the 2018 Classification of Periodontal and Peri-Implant Diseases and Conditions. Samples were processed using high-throughput sequencing technologies (Illumina MiSeq). Taxa differentially abundant were identified using Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC). α- and β-diversity metrics were calculated using q2-diversity in QIIME2. The analyses were adjusted for age, gender and smoking status.

RESULTS

The identified subgingival microbiome showed statistically significant differences among subjects, categorized into periodontal health, gingivitis and stages I-II and III-IV periodontitis (p < .05). In patients with severe (stages III-IV) periodontitis, the genera Filifactor and Fretibacterium were detected 24 times more frequently than in periodontally healthy subjects. Similarly, the genera Porphyromonas, Prevotella and Tannerella were detected four times more frequently (p < .05). The genera Granulicatella, Streptococcus, Paracoccus, Pseudomonas, Haemophilus, Actinobacteria, Bergeyella and Capnocytophaga were significantly associated with healthier periodontal status (p < .05).

CONCLUSIONS

Significant differences were detected in the subgingival microbiome among periodontal health, gingivitis and stages I-II or III-IV periodontitis, suggesting overlapping, yet distinguishable microbial profiles.

Suspension of oral hygiene practices highlights key bacterial shifts in saliva, tongue, and tooth plaque during gingival inflammation and resolution

Experimentally induced gingivitis is associated with inflammatory and microbiological changes in an otherwise healthy subject, demonstrating the impacts of discontinuing oral hygiene routines. Understanding the bacterial dynamics during the induction and resolution of gingival inflammation will aid in the development of bacterial prognostic tests and probiotics for severe oral disease. We profiled the bacterial community in 15 healthy subjects who suspended all oral-hygiene practices for three weeks. Saliva, tongue, subgingival, and supragingival plaque samples were collected over seven weeks and showed a return to community baseline after oral hygiene practices were resumed. Stronger temporal changes in subgingival and supragingival plaque suggest these sample types may be preferred over saliva or tongue plaque for future prognostics. Taxonomic groups spanning ten phyla demonstrated consistent abundance shifts, including a significant decrease in Streptococcus, Neisseria, and Actinomyces populations, and an increase in Prevotella, Fusobacterium, and Porphyromonas populations. With four distinct oral sites surveyed and results mapped to the Human Oral Microbiome Database reference set, this work provides a comprehensive taxonomic catalog of the bacterial shifts observed during the onset and resolution of gingival inflammation.

Impact of Growth Rate on the Protein-mRNA Ratio in Pseudomonas aeruginosa

Our understanding of how bacterial pathogens colonize and persist during human infection has been hampered by the limited characterization of bacterial physiology during infection and a research bias toward in vitro, fast-growing bacteria. Recent research has begun to address these gaps in knowledge by directly quantifying bacterial mRNA levels during human infection, with the goal of assessing microbial community function at the infection site. However, mRNA levels are not always predictive of protein levels, which are the primary functional units of a cell. Here, we used carefully controlled chemostat experiments to examine the relationship between mRNA and protein levels across four growth rates in the bacterial pathogen Pseudomonas aeruginosa. We found a genome-wide positive correlation between mRNA and protein abundances across all growth rates, with genes required for P. aeruginosa viability having stronger correlations than nonessential genes. We developed a statistical method to identify genes whose mRNA abundances poorly predict protein abundances and calculated an RNA-to-protein (RTP) conversion factor to improve mRNA predictions of protein levels. The application of the RTP conversion factor to publicly available transcriptome data sets was highly robust, enabling the more accurate prediction of P. aeruginosa protein levels across strains and growth conditions. Finally, the RTP conversion factor was applied to P. aeruginosa human cystic fibrosis (CF) infection transcriptomes to provide greater insights into the functionality of this bacterium in the CF lung. This study addresses a critical problem in infection microbiology by providing a framework for enhancing the functional interpretation of bacterial human infection transcriptome data. IMPORTANCE Our understanding of bacterial physiology during human infection is limited by the difficulty in assessing bacterial function at the infection site. Recent studies have begun to address this question by quantifying bacterial mRNA levels in human-derived samples using transcriptomics. One challenge for these studies is the poor predictivity of mRNA for protein levels for some genes. Here, we addressed this challenge by measuring the transcriptomes and proteomes of P. aeruginosa grown at four growth rates. Our results revealed that the growth rate does not impact the genome-wide correlation of mRNA and protein levels. We used statistical methods to identify the genes for which mRNA and protein were poorly correlated and developed an RNA-to-protein (RTP) conversion factor that improved the predictivity of protein levels across strains and growth conditions. Our results provide new insights into mRNA-protein correlations and tools to enhance our understanding of bacterial physiology from transcriptome data.

Understanding human health through metatranscriptomics

Metatranscriptomics has revolutionized our ability to explore and understand transcriptional programs in microbial communities. Moreover, it has enabled us to gain deeper and more specific insight into the microbial activities in human gut, respiratory, oral, and vaginal communities. Perhaps the most important contribution of metatranscriptomics arises, however, from the analyses of disease-associated communities. We review the advantages and disadvantages of metatranscriptomics analyses in understanding human health and disease. We focus on human tissues low in microbial biomass and conditions associated with dysbiotic microbiota. We conclude that a more widespread use of metatranscriptomics and increased knowledge on microbe activities will uncover critical interactions between microbes and host in human health and provide diagnostic basis for culturing-independent, direct functional pathogen identification.

The hitchhikers' guide to RNA sequencing and functional analysis

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

Microbiome and Human Health: Current Understanding, Engineering, and Enabling Technologies

The human microbiome is composed of a collection of dynamic microbial communities that inhabit various anatomical locations in the body. Accordingly, the coevolution of the microbiome with the host has resulted in these communities playing a profound role in promoting human health. Consequently, perturbations in the human microbiome can cause or exacerbate several diseases. In this Review, we present our current understanding of the relationship between human health and disease development, focusing on the microbiomes found across the digestive, respiratory, urinary, and reproductive systems as well as the skin. We further discuss various strategies by which the composition and function of the human microbiome can be modulated to exert a therapeutic effect on the host. Finally, we examine technologies such as multiomics approaches and cellular reprogramming of microbes that can enable significant advancements in microbiome research and engineering.

Effects of oral health intervention strategies on cognition and microbiota alterations in patients with mild Alzheimer's disease: A randomized controlled trial

We explored the effects of an oral health intervention on the oral microbiome and cognitive function of patients with mild Alzheimer's disease (AD) and determined the influence on disease progression. Sixty-six patients with mild AD were randomly assigned to intervention or control groups and received a 24-week oral health intervention and routine care, respectively. Data were collected at baseline and week 24. 16 S rRNA sequencing was used to analyze oral microbiota. After 24 weeks of oral health intervention, Kayser-Jones Brief Oral Health Status Examination (BOHSE), Mini-Mental State Examination (MMSE), Neuropsychiatric Inventory (NPI), Nursing Home Adjustment Scale (NHAS), and Alzheimer's Disease Cooperative Study-ADL (ADCS-ADL) scores were different between groups (p < 0.05). Subgingival plaque in patients with AD showed significant differences in the diversity and abundance of oral microbiomes, with a higher abundance of normal oral flora in the intervention group. We found oral health intervention strategies are effective in modifying subgingival microbiota differences and slowing cognitive decline in mild AD patients.

Functional signatures of ex-vivo dental caries onset

Background

The etiology of dental caries remains poorly understood. With the advent of next-generation sequencing, a number of studies have focused on the microbial ecology of the disease. However, taxonomic associations with caries have not been consistent. Researchers have also pursued function-centric studies of the caries microbial communities aiming to identify consistently conserved functional pathways. A major question is whether changes in microbiome are a cause or a consequence of the disease. Thus, there is a critical need to define conserved functional signatures at the onset of dental caries.

Methods

Since it is unethical to induce carious lesions clinically, we developed an innovative longitudinal ex-vivo model integrated with the advanced non-invasive multiphoton second harmonic generation bioimaging to spot the very early signs of dental caries, combined with 16S rRNA short amplicon sequencing and liquid chromatography-mass spectrometry-based targeted metabolomics.

Findings

For the first time, we induced longitudinally monitored caries lesions validated with the scanning electron microscope. Consequently, we spotted the caries onset and, associated with it, distinguished five differentiating metabolites - Lactate, Pyruvate, Dihydroxyacetone phosphate, Glyceraldehyde 3-phosphate (upregulated) and Fumarate (downregulated). Those metabolites co-occurred with certain bacterial taxa; Streptococcus, Veillonella, Actinomyces, Porphyromonas, Fusobacterium, and Granulicatella, regardless of the abundance of other taxa.

Interpretation

These findings are crucial for understanding the etiology and dynamics of dental caries, and devising targeted interventions to prevent disease progression.

In vitro activity of anti-rheumatic drugs on release of pro-inflammatory cytokines from oral cells in interaction with microorganisms

Periodontitis patients suffering concomitantly from rheumatoid arthritis (RA) often present with less inflamed periodontal tissues due to the ongoing anti-rheumatic therapy. This in vitro study was aimed to analyze whether anti-inflammatory drugs used in the therapy of RA can modulate the release of IL-8 and IL-1β by professional and non-professional immune cells stimulated with microorganisms. Periodontal ligament (PDL) fibroblasts, monocytic MONO-MAC-6-cells, and gingival keratinocytes were exposed to ibuprofen, prednisolone, and methotrexate with and without lysates of Fusobacterium nucleatum or Candida albicans. Supernatants were obtained and the levels of interleukin(IL)-8 and IL-1β (only MONO-MAC-6) were quantified. The addition of F. nucleatum lysate resulted in the strongest release of proinflammatory cytokines by PDL fibroblast and MONO-MAC-6 cells, while the modification by the tested anti-rheumatic drugs was only minor. After stimulation of the MONO-MAC-cells with F. nucleatum, prednisolone increased the release of IL-8, whereas methotrexate decreased the level. Anti-inflammatory drugs increased the adherence of C. albicans to epithelial cells. In patients with RA, the reduction of the microbial load in subgingival biofilm (biofilm removal) is of major importance; however, the intake of inflammatory drugs may interfere with the inflammatory response.

Ecological Effects of Daily Antiseptic Treatment on Microbial Composition of Saliva-Grown Microcosm Biofilms and Selection of Resistant Phenotypes

Antiseptics are widely used in dental practice and included in numerous over-the-counter oral care products. However, the effects of routine antiseptic use on microbial composition of oral biofilms and on the emergence of resistant phenotypes remain unclear. Microcosm biofilms were inoculated from saliva samples of four donors and cultured in the Amsterdam Active Attachment biofilm model for 3 days. Then, they were treated two times daily with chlorhexidine digluconate (CHX) or cetylpyridinium chloride (CPC) for a period of 7 days. Ecological changes upon these multiple antiseptic treatments were evaluated by semiconductor-based sequencing of bacterial 16S rRNA genes and identification of amplicon sequence variants (ASVs). Furthermore, culture-based approaches were used for colony-forming units (CFU) assay, identification of antiseptic-resistant phenotypes using an agar dilution method, and evaluation of their antibiotic susceptibilities. Both CHX and CPC showed only slight effects on CFU and could not inhibit biofilm growth despite the two times daily treatment for 7 days. Both antiseptics showed significant ecological effects on the microbial compositions of the surviving microbiota, whereby CHX led to enrichment of rather caries-associated saccharolytic taxa and CPC led to enrichment of rather gingivitis-associated proteolytic taxa. Antiseptic-resistant phenotypes were isolated on antiseptic-containing agar plates, which also exhibited phenotypic resistance to various antibiotics. Our results highlight the need for further research into potential detrimental effects of antiseptics on the microbial composition of oral biofilms and on the spread of antimicrobial resistance in the context of their frequent use in oral healthcare.

Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era

Despite significant healthcare advances in the 21st century, the exact etiology of dental caries remains unsolved. The past two decades have witnessed a tremendous growth in our understanding of dental caries amid the advent of revolutionary omics technologies. Accordingly, a consensus has been reached that dental caries is a community-scale metabolic disorder, and its etiology is beyond a single causative organism. This conclusion was based on a variety of microbiome studies following the flow of information along the central dogma of biology from genomic data to the end products of metabolism. These studies were facilitated by the unprecedented growth of the next- generation sequencing tools and omics techniques, such as metagenomics and metatranscriptomics, to estimate the community composition of oral microbiome and its functional potential. Furthermore, the rapidly evolving proteomics and metabolomics platforms, including nuclear magnetic resonance spectroscopy and/or mass spectrometry coupled with chromatography, have enabled precise quantification of the translational outcomes. Although the majority supports 'conserved functional changes' as indicators of dysbiosis, it remains unclear how caries dynamics impact the microbiota functions and vice versa, over the course of disease onset and progression. What compounds the situation is the host-microbiota crosstalk. Genome-wide association studies have been undertaken to elucidate the interaction of host genetic variation with the microbiome. However, these studies are challenged by the complex interaction of host genetics and environmental factors. All these complementary approaches need to be orchestrated to capture the key players in this multifactorial disease. Herein, we critically review the milestones in caries research focusing on the state-of-art singular and integrative omics studies, supplemented with a bibliographic network analysis to address the oral microbiome, the host factors, and their interactions. Additionally, we highlight gaps in the dental literature and shed light on critical future research questions and study designs that could unravel the complexities of dental caries, the most globally widespread disease.

Diurnal and eating-associated microbial patterns revealed via high-frequency saliva sampling

The oral microbiome is linked to oral and systemic health, but its fluctuation under frequent daily activities remains elusive. Here, we sampled saliva at 10- to 60-min intervals to track the high-resolution microbiome dynamics during the course of human activities. This dense time series data showed that eating activity markedly perturbed the salivary microbiota, with tongue-specific Campylobacter concisus and Oribacterium sinus and dental plaque-specific Lautropia mirabilis, Rothia aeria, and Neisseria oralis increased after every meal in a temporal order. The observation was reproducible in multiple subjects and across an 11-mo period. The microbiome composition showed significant diurnal oscillation patterns at different taxonomy levels with Prevotella/Alloprevotella increased at night and Bergeyella HMT 206/Haemophilus slowly increased during the daytime. We also identified microbial co-occurring patterns in saliva that are associated with the intricate biogeography of the oral microbiome. Microbial source tracking analysis showed that the contributions of distinct oral niches to the salivary microbiome were dynamically affected by daily activities, reflecting the role of saliva in exchanging microbes with other oral sites. Collectively, our study provides insights into the temporal microbiome variation in saliva and highlights the need to consider daily activities and diurnal factors in design of oral microbiome studies.

Polymicrobial Interactions of Oral Microbiota: a Historical Review and Current Perspective

The oral microbiota is enormously diverse, with over 700 microbial species identified across individuals that play a vital role in the health of our mouth and our overall well-being. In addition, as oral diseases such as caries (cavities) and periodontitis (gum disease) are mediated through interspecies microbial interactions, this community serves as an important model system to study the complexity and dynamics of polymicrobial interactions. Here, we review historical and recent progress in our understanding of the oral microbiome, highlighting how oral microbiome research has significantly contributed to our understanding of microbial communities, with broad implications in polymicrobial diseases and across microbial community ecology. Further, we explore innovations and challenges associated with analyzing polymicrobial systems and suggest future directions of study. Finally, we provide a conceptual framework to systematically study microbial interactions within complex communities, not limited to the oral microbiota.

Associations between inflammation-related LL-37 with subgingival microbial dysbiosis in rheumatoid arthritis patients

OBJECTIVE

This study investigated the subgingival microbial profile of rheumatoid arthritis (RA) patients and its associations with disease parameters and the inflammation-related antimicrobial peptide, LL-37.

METHODS

RA and non-RA (NRA) patients were assessed for periodontal status and divided into periodontitis (CP), gingivitis (G), and healthy (H) groups. Subgingival plaque 16s rRNA gene sequencing data was processed and analyzed using the CLC Genomic Workbench (Qiagen). Bacterial diversity and co-occurrence patterns were examined. Differential abundance between groups was also investigated. Associations between bacterial genera with disease parameters and LL-37 levels were explored qualitatively using canonical correlation analysis.

RESULTS

Subgingival microbial community clustered in CP status. Co-occurrence network in NRA-H was dominated by health-associated genera, while the rest of the networks' key genera were both health- and disease-associated. RA-CP displayed highly inter-generic networks with a statistically significant increase in periodontal disease-associated genera (p<0.05). In NRA-H, disease parameters and LL-37 were correlated positively with disease-associated genera while negatively with health-associated genera. However, in the remaining groups, mixed positive and negative correlations were noted with genera.

CONCLUSION

RA patients demonstrated subgingival microbial dysbiosis where the bacteria networks were dominated by health- and disease-associated genera. Mixed correlations with disease parameters and LL-37 levels were noted.

CLINICAL RELEVANCE

The subgingival microbial dysbiosis in RA may predispose these patients to developing periodontal inflammation with an associated detrimental effect on host immune responses. Routine periodontal assessment may allow initiation of treatment strategies to minimize the effects of gingival inflammation on the existing heightened immune response present in RA patients.

Determinants and Interactions of Oral Bacterial and Fungal Microbiota in Healthy Chinese Adults

Numerous studies have examined the composition of and factors shaping the oral bacterial microbiota in healthy adults; however, similar studies on the less dominant yet ecologically and clinically important fungal microbiota are scarce. In this study, we characterized simultaneously the oral bacterial and fungal microbiomes in a large cohort of systemically healthy Chinese adults by sequencing the bacterial 16S rRNA gene and fungal internal transcribed spacer. We showed that different factors shaped the oral bacterial and fungal microbiomes in healthy adults. Sex and age were associated with the alpha diversity of the healthy oral bacterial microbiome but not that of the fungal microbiome. Age was also a major factor affecting the beta diversity of the oral bacterial microbiome; however, it only exerted a small effect on the oral fungal microbiome when compared with other variables. After controlling for age and sex, the bacterial microbiota structure was most affected by marital status, recent oral conditions and oral hygiene-related factors, whereas the fungal microbiota structure was most affected by education level, fruits and vegetables, and bleeding gums. Bacterial-fungal interactions were limited in the healthy oral microbiota, with the strongest association existing between Pseudomonas sp. and Rhodotorula dairenensis. Several bacterial amplicon sequence variants (ASVs) belonging to Veillonella atypica and the genera Leptotrichia, Streptococcus and Prevotella_7 and fungal ASVs belonging to Candida albicans and the genus Blumeria were revealed as putative pivotal members of the healthy oral microbiota. Overall, our study has facilitated understanding of the determining factors and cross-kingdom interactions of the healthy human oral microbiome. IMPORTANCE Numerous studies have examined the bacterial community residing in our oral cavity; however, information on the less dominant yet ecologically and clinically important fungal members is limited. In this study, we characterized simultaneously the oral bacterial and fungal microbial communities in a large cohort of healthy Chinese adults, examined their associations with an array of host factors, and explored potential interactions between the two microbial groups. We showed that different factors shape the diversity and structure of the oral bacterial and fungal microbial communities in healthy adults, with, for instance, sex and age only associated with the diversity of the bacterial community but not that of the fungal community. Besides, we found that bacterial-fungal interactions are limited in the healthy oral cavity. Overall, our study has facilitated understanding of the determining factors and bacterial-fungal interactions of the healthy human oral microbial community.

A quantitative framework reveals traditional laboratory growth is a highly accurate model of human oral infection

Bacterial behavior and virulence during human infection is difficult to study and largely unknown, as our vast knowledge of infection microbiology is primarily derived from studies using in vitro and animal models. Here, we characterize the physiology of Porphyromonas gingivalis, a periodontal pathogen, in its native environment using 93 published metatranscriptomic datasets from periodontally healthy and diseased individuals. P. gingivalis transcripts were more abundant in samples from periodontally diseased patients but only above 0.1% relative abundance in one-third of diseased samples. During human infection, P. gingivalis highly expressed genes encoding virulence factors such as fimbriae and gingipains (proteases) and genes involved in growth and metabolism, indicating that P. gingivalis is actively growing during disease. A quantitative framework for assessing the accuracy of model systems showed that 96% of P. gingivalis genes were expressed similarly in periodontitis and in vitro midlogarithmic growth, while significantly fewer genes were expressed similarly in periodontitis and in vitro stationary phase cultures (72%) or in a murine abscess infection model (85%). This high conservation in gene expression between periodontitis and logarithmic laboratory growth is driven by overall low variance in P. gingivalis gene expression, relative to other pathogens including Pseudomonas aeruginosa and Staphylococcus aureus Together, this study presents strong evidence for the use of simple test tube growth as the gold standard model for studying P. gingivalis biology, providing biological relevance for the thousands of laboratory experiments performed with logarithmic phase P. gingivalis Furthermore, this work highlights the need to quantitatively assess the accuracy of model systems.

Droplet-based microsystems as novel assessment tools for oral microbial dynamics

The human microbiome comprises thousands of microbial species that live in and on the body and play critical roles in human health and disease. Recent findings on the interplay among members of the oral microbiome, defined by a personalized set of microorganisms, have elucidated the role of bacteria and yeasts in oral health and diseases including dental caries, halitosis, and periodontal infections. However, the majority of these studies rely on traditional culturing methods which are limited in their ability of replicating the oral microenvironment, and therefore fail to evaluate key microbial interactions in microbiome dynamics. Novel culturing methods have emerged to address this shortcoming. Here, we reviewed the potential of droplet-based microfluidics as an alternative approach for culturing microorganisms and assessing the oral microbiome dynamics. We discussed the state of the art and recent progress in the field of oral microbiology. Although at its infancy, droplet-based microtechnology presents an interesting potential for elucidating oral microbial dynamics and pathophysiology. We highlight how new findings provided by current microfluidic-based methodologies could advance the investigation of the oral microbiome. We anticipate that our work involving the droplet-based microfluidic technique with a semipermeable membrane will lay the foundations for future microbial dynamics studies and further expand the knowledge of the oral microbiome and its implication in oral health.

Discrimination of Bacterial Community Structures among Healthy, Gingivitis, and Periodontitis Statuses through Integrated Metatranscriptomic and Network Analyses

Periodontal disease is an inflammatory condition caused by polymicrobial infection. The inflammation is initiated at the gingiva (gingivitis) and then extends to the alveolar bone, leading to tooth loss (periodontitis). Previous studies have shown differences in bacterial composition between periodontal healthy and diseased sites. However, bacterial metabolic activities during the health-to-periodontitis microbiome shift are still inadequately understood. This study was performed to investigate the bacterial characteristics of healthy, gingivitis, and periodontitis statuses through metatranscriptomic analysis. Subgingival plaque samples of healthy, gingivitis, and periodontitis sites in the same oral cavity were collected from 21 patients. Bacterial compositions were then determined based on 16S rRNA reads; taxonomic and functional profiles derived from genes based on mRNA reads were estimated. The results showed clear differences in bacterial compositions and functional profiles between healthy and periodontitis sites. Co-occurrence networks were constructed for each group by connecting two bacterial species if their mRNA abundances were positively correlated. The clustering coefficient values were 0.536 for healthy, 0.600 for gingivitis, and 0.371 for periodontitis sites; thus, network complexity increased during gingivitis development, whereas it decreased during progression to periodontitis. Taxa, including Eubacterium nodatum, Eubacterium saphenum, Filifactor alocis, and Fretibacterium fastidiosum, showed greater transcriptional activities than those of red complex bacteria, in conjunction with disease progression. These taxa were associated with periodontal disease progression, and the health-to-periodontitis microbiome shift was accompanied by alterations in bacterial network structure and complexity.

IMPORTANCE The characteristics of the periodontal microbiome influence clinical periodontal status. Gingivitis involves reversible gingival inflammation without alveolar bone resorption. In contrast, periodontitis is an irreversible disease characterized by inflammatory destruction in both soft and hard tissues. An imbalance of the microbiome is present in both gingivitis and periodontitis. However, differences in microbiomes and their functional activities in the healthy, gingivitis, and periodontitis statuses are still inadequately understood. Furthermore, some inflamed gingival statuses do not consistently cause attachment loss. In this study, metatranscriptomic analyses were used to investigate the specific bacterial composition and gene expression patterns of the microbiomes of the healthy, gingivitis, and periodontitis statuses. In addition, co-occurrence network analysis revealed that the gingivitis site included features of networks observed in both the healthy and periodontitis sites. These results provide transcriptomic evidence to support gingivitis as an intermediate state between the healthy and periodontitis statuses.

Metatranscriptomic Analysis of Human Lung Metagenomes from Patients with Lung Cancer

This study was designed to characterize the microbiomes of the lung tissues of lung cancer patients. RNA-sequencing was performed on lung tumor samples from 49 patients with lung cancer. Metatranscriptomics data were analyzed using SAMSA2 and Kraken2 software. 16S rRNA sequencing was also performed. The heterogeneous cellular landscape and immune repertoires of the lung samples were examined using xCell and TRUST4, respectively. We found that nine bacteria were significantly enriched in the lung tissues of cancer patients, and associated with reduced overall survival (OS). We also found that subjects with mutations in the epidermal growth factor receptor gene were less likely to experience the presence of Pseudomonas. aeruginosa. We found that the presence of CD8+ T-cells, CD4+ naive T-cells, dendritic cells, and CD4+ central memory T cells were associated with a good prognosis, while the presence of pro B-cells was associated with a poor prognosis. Furthermore, high clone numbers were associated with a high ImmuneScore for all immune receptor repertoires. Clone numbers and diversity were significantly higher in unpresented subjects compared to presented subjects. Our results provide insight into the microbiota of human lung cancer, and how its composition is linked to the tumor immune microenvironment, immune receptor repertoires, and OS.

A Trifecta of New Insights into Ovine Footrot for Infection Drivers, Immune Response, and Host-Pathogen Interactions

Footrot is a polymicrobial infectious disease in sheep causing severe lameness, leading to one of the industry's largest welfare problems. The complex etiology of footrot makes in situ or in vitro investigations difficult. Computational methods offer a solution to understanding the bacteria involved and how they may interact with the host, ultimately providing a way to identify targets for future hypothesis-driven investigative work. Here, we present the first combined global analysis of bacterial community transcripts together with the host immune response in healthy and diseased ovine feet during a natural polymicrobial infection state using metatranscriptomics. The intratissue and surface bacterial populations and the most abundant bacterial transcriptomes were analyzed, demonstrating that footrot-affected skin has reduced diversity and increased abundances of not only the causative bacterium Dichelobacter nodosus but also other species such as Mycoplasma fermentans and Porphyromonas asaccharolytica. Host transcriptomics reveals the suppression of biological processes related to skin barrier function, vascular functions, and immunosurveillance in unhealthy interdigital skin, supported by histological findings that type I collagen (associated with scar tissue formation) is significantly increased in footrot-affected interdigital skin compared to outwardly healthy skin. Finally, we provide some interesting indications of host and pathogen interactions associated with virulence genes and the host spliceosome, which could lead to the identification of future therapeutic targets.

Calprotectin (S100A8/A9) Is an Innate Immune Effector in Experimental Periodontitis

Upregulated in inflammation, calprotectin (complexed S100A8 and S100A9; S100A8/A9) functions as an innate immune effector molecule, promoting inflammation, and also as an antimicrobial protein. We hypothesized that antimicrobial S100A8/A9 would mitigate change to the local microbial community and promote resistance to experimental periodontitis in vivo. To test this hypothesis, S100A9-/- and wild-type (WT; S100A9+/+) C57BL/6 mice were compared using a model of ligature-induced periodontitis. On day 2, WT mice showed fewer infiltrating innate immune cells than S100A9-/- mice; by day 5, the immune cell numbers were similar. At 5 days post ligature placement, oral microbial communities sampled with swabs differed significantly in beta diversity between the mouse genotypes. Ligatures recovered from molar teeth of S100A9-/- and WT mice contained significantly dissimilar microbial genera from each other and the overall oral communities from swabs. Concomitantly, the S100A9-/- mice had significantly greater alveolar bone loss than WT mice around molar teeth in ligated sites. When the oral microflora was ablated by antibiotic pretreatment, differences disappeared between WT and S100A9-/- mice in their immune cell infiltrates and alveolar bone loss. Calprotectin, therefore, suppresses emergence of a dysbiotic, proinflammatory oral microbial community, which reduces innate immune effector activity, including early recruitment of innate immune cells, mitigating subsequent alveolar bone loss and protecting against experimental periodontitis.

β-Glycyrrhetinic acid inhibits the bacterial growth and biofilm formation by supragingival plaque commensals

β-Glycyrrhetinic acid (BGA) is a natural antibacterial agent. Previous studies reported that BGA has antibacterial effects against several bacteria. This study evaluated the effects of BGA on the regulation of supragingival plaque bacteria. First, the minimum inhibitory concentrations (MICs) of BGA against oral bacteria were measured. Next, the minimum concentrations for inhibition of biofilm formation were evaluated against Streptococcus mutans and Streptococcus sobrinus, possessing insoluble glucan synthesis abilities. The MICs of biofilm formation by these bacteria ranged from 1/8 to 2× MIC. Furthermore, the inhibition effects of BGA against the coaggregation of Porphyromonas gingivalis and Streptococcus gordonii were evaluated. BGA at 32 or 64 μg/mL inhibited the coaggregation of these bacteria after a 30 min incubation. Lastly, the inhibition effects of BGA against human supragingival plaque bacteria were evaluated. Human supragingival plaque samples were obtained from 12 healthy donors. The inhibition effects of BGA against biofilm formation by these plaque bacteria were evaluated. Of 12 samples, the biofilm formation by 11 was significantly attenuated by 128-256 μg/mL of BGA. The number of colony forming units in these biofilms was also significantly attenuated. In conclusion, it was revealed that BGA inhibits the growth and biofilm formation of bacteria, furthermore, the same effect was confirmed with supragingival plaque bacteria. BGA is a good candidate for a natural agent that prevents the outbreak and progression of periodontal disease because it suppresses not only the growth and biofilm formation of bacteria, but also the coaggregation of P. gingivalis with plaque bacteria.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Recent progress in analyzing the spatial structure of the human microbiome: distinguishing biogeography and architecture in the oral and gut communities

Fueled by technological advances in methods for sample collection and preservation in sequencing studies, and in advances in computational analyses of high content image data, the spatial structure of the human microbiome is coming to light. In this mini-review, we summarize recent developments in our understanding of the structure of two human microbiomes: the lower gut and the oral cavity. We focus on only the most recent literature and we make an important distinction between two forms of spatial structure, governed by scale: biogeography and architecture. By segmenting the study of microbiome spatial structure into two categories, we demonstrate the potential to greatly advance our understanding of the mechanistic principles that link structure and function in the microbiome.

Resolving the Contradictory Functions of Lysine Decarboxylase and Butyrate in Periodontal and Intestinal Diseases

Periodontal disease is a common, bacterially mediated health problem worldwide. Mastication (chewing) repeatedly traumatizes the gingiva and periodontium, causing traces of inflammatory exudate, gingival crevicular fluid (GCF), to appear in crevices between the teeth and gingiva. Inadequate tooth cleaning causes a dentally adherent microbial biofilm composed of commensal salivary bacteria to appear around these crevices where many bacteria grow better on GCF than in saliva. We reported that lysine decarboxylase (Ldc) from Eikenella corrodens depletes the GCF of lysine by converting it to cadaverine and carbon dioxide. Lysine is an amino acid essential for the integrity and continuous renewal of dentally attached epithelium acting as a barrier to microbial products. Unless removed regularly by oral hygiene, bacterial products invade the lysine-deprived dental attachment where they stimulate inflammation that enhances GCF exudation. Cadaverine increases and supports the development of a butyrate-producing microbiome that utilizes the increased GCF substrates to slowly destroy the periodontium (dysbiosis). A long-standing paradox is that acid-induced Ldc and butyrate production support a commensal (probiotic) microbiome in the intestine. Here, we describe how the different physiologies of the respective tissues explain how the different Ldc and butyrate functions impact the progression and control of these two chronic diseases.

A salivary microbiome-based auxiliary diagnostic model for type 2 diabetes mellitus

OBJECTIVE

Studies have shown that oral microbiota composition is altered in type 2 diabetes mellitus, implying that it is a potential biomarker for diabetes. This study aimed at constructing a noninvasive auxiliary diagnostic model for diabetes based on differences in the salivary microbial community.

DESIGN

Salivary microbiota from 24 treatment-naive type 2 diabetes mellitus patients and 21 healthy populations were detected through 16S rRNA gene sequencing, targeting the V3/V4 region using the MiSeq platform. Salivary microbiome diversity and composition were analyzed so as to establish a diagnostic model for type 2 diabetes.

RESULTS

Salivary microbiome for treatment-naive type 2 diabetes mellitus patients was imbalanced with certain taxa, including Slackia, Mitsuokella, Abiotrophia, and Parascardovia that being significantly dominant, while the abundance of Moraxella was high in healthy controls. Diabetic patients exhibited varying levels of Prevotella nanceiensis and Prevotella melaninogenica which were negatively correlated with glycosylated hemoglobin and fasting blood glucose levels, as well as fasting blood glucose levels, respectively. Based on differences in salivary microbiome composition between diabetic and healthy groups, we developed a diagnostic model that can be used for the auxiliary diagnosis of type 2 diabetes mellitus with an accuracy of 80 %.

CONCLUSIONS

These findings elucidate on the differences in salivary microbiome compositions between type 2 diabetic and non-diabetic populations, and the diagnostic model provides a promising approach for the noninvasive auxiliary diagnosis of diabetes mellitus.

Longitudinal Multi-omics and Microbiome Meta-analysis Identify an Asymptomatic Gingival State That Links Gingivitis, Periodontitis, and Aging

A significant portion of world population still fails to brush teeth daily. As a result, the majority of the global adult population is afflicted with chronic gingivitis, and if it is left untreated, some of them will eventually suffer from periodontitis.

Most adults experience episodes of gingivitis, which can progress to the irreversible, chronic state of periodontitis, yet roles of plaque in gingivitis onset and progression to periodontitis remain elusive. Here, we longitudinally profiled the plaque metagenome, the plaque metabolome, and salivary cytokines in 40 adults who transited from naturally occurring gingivitis (NG) to healthy gingivae (baseline) and then to experimental gingivitis (EG). During EG, rapid and consistent alterations in plaque microbiota, metabolites, and salivary cytokines emerged as early as 24 to 72 h after oral-hygiene pause, defining an asymptomatic suboptimal health (SoH) stage of the gingivae. SoH features a swift, full activation of 11 salivary cytokines but a steep synergetic decrease of plaque-derived betaine and Rothia spp., suggesting an anti-gum inflammation mechanism by health-promoting symbionts. Global, cross-cohort meta-analysis revealed, at SoH, a greatly elevated microbiome-based periodontitis index driven by its convergence of both taxonomical and functional profiles toward the periodontitis microbiome. Finally, post-SoH gingivitis development accelerates oral microbiota aging by over 1 year within 28 days, with Rothia spp. depletion and Porphyromonas gingivalis elevation as hallmarks. Thus, the microbiome-defined, transient gum SoH stage is a crucial link among gingivitis, periodontitis, and aging.

Effects of altitude on human oral microbes

Human oral microbes play a vital role maintaining host metabolic homeostasis. The Qinghai-Tibet Plateau is mainly characterized by a high altitude, dry, cold, and hypoxic environment. The oral microbiota is subject to selective pressure from the plateau environment, which affects oral health. Only a few studies have focused on the characteristics of oral microbiota in high-altitude humans. We collected saliva samples from 167 Tibetans at four altitudes (2800 to 4500 m) in Tibet to explore the relationship between the high altitude environment and oral microbiota. We conducted a two (high- and ultra-high-altitude) group analysis based on altitude, and adopted the 16S rRNA strategy for high-throughput sequencing. The results show that the alpha diversity of the oral microbiota decreased with altitude, whereas beta diversity increased with altitude. A LEfSe analysis revealed that the oral microbial biomarker of the high-altitude group (< 3650 m) was Streptococcus, and the biomarker of the ultra-high-altitude group (> 4000 m) was Prevotella. The relative abundance of Prevotella increased with altitude, whereas the relative abundance of Streptococcus decreased with altitude. A network analysis showed that the microbial network structure was more compact and complex, and the interaction between the bacterial genera was more intense in the high altitude group. Gene function prediction results showed that the amino acid and vitamin metabolic pathways were upregulated in the ultra-high-altitude group. These result show that altitude is an important factor affecting the diversity and community structure of the human oral microbiota.

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.

Impaired host response and the presence of Acinetobacter baumannii in the serum microbiome of type-II diabetic patients

Type II diabetes (T2D) affects over 10% of the US population and is a growing disease worldwide that manifests with numerous comorbidities and defects in inflammation. This dysbiotic host response allows for infection of the host by numerous microorganisms. In the course of T2D disease, individuals can develop chronic infections including foot ulcers and periodontitis, which lead to further complications and opportunistic infections in multiple body sites. In this study, we investigated the serum of healthy subjects and patients with T2D with (T2DP) or without periodontitis for both microbiome signatures in addition to cytokine profiles. Surprisingly, we detected the presence of Acinetobacter baumanii in the serum of 23% individuals with T2D/T2DP tested. In T2DP, IL-1β, TNF-α, MCP-1, IL-6, IL-8, and IFN-γ were significantly elevated in ABC-positive subjects. As an emerging pathogen, A. baumanii infection represents a risk for impaired inflammation and the development of comorbidities in subjects with T2D.

Oral microbiome interactions with gingival gene expression patterns for apoptosis, autophagy and hypoxia pathways in progressing periodontitis

Oral mucosal tissues must react with and respond to microbes comprising the oral microbiome ecology. This study examined the interaction of the microbiome with transcriptomic footprints of apoptosis, autophagy and hypoxia pathways during periodontitis. Adult Macaca mulatta (n = 18; 12-23 years of age) exhibiting a healthy periodontium at baseline were used to induce progressing periodontitis through ligature placement around premolar/molar teeth. Gingival tissue samples collected at baseline, 0·5, 1 and 3 months of disease and at 5 months for disease resolution were analysed via microarray. Bacterial samples were collected at identical sites to the host tissues and analysed using MiSeq. Significant changes in apoptosis and hypoxia gene expression occurred with initiation of disease, while autophagy gene changes generally emerged later in disease progression samples. These interlinked pathways contributing to cellular homeostasis showed significant correlations between altered gene expression profiles in apoptosis, autophagy and hypoxia with groups of genes correlated in different directions across health and disease samples. Bacterial complexes were identified that correlated significantly with profiles of host genes in health, disease and resolution for each pathway. These relationships were more robust in health and resolution samples, with less bacterial complex diversity during disease. Using these pathways as cellular responses to stress in the local periodontal environment, the data are consistent with the concept of dysbiosis at the functional genomics level. It appears that the same bacteria in a healthy microbiome may be interfacing with host cells differently than in a disease lesion site and contributing to the tissue destructive processes.

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.

Ignoring social distancing: advances in understanding multi-species bacterial interactions

Almost every ecosystem on this planet is teeming with microbial communities made of diverse bacterial species. At a reductionist view, many of these bacteria form pairwise interactions, but, as the field of view expands, the neighboring organisms and the abiotic environment can play a crucial role in shaping the interactions between species. Over the years, a strong foundation of knowledge has been built on isolated pairwise interactions between bacteria, but now the field is advancing toward understanding how cohabitating bacteria and natural surroundings affect these interactions. Use of bottom-up approaches, piecing communities together, and top-down approaches that deconstruct communities are providing insight on how different species interact. In this review, we highlight how studies are incorporating more complex communities, mimicking the natural environment, and recurring findings such as the importance of cooperation for stability in harsh environments and the impact of bacteria-induced environmental pH shifts. Additionally, we will discuss how omics are being used as a top-down approach to identify previously unknown interspecies bacterial interactions and the challenges of these types of studies for microbial ecology.

The Oral Host-Microbial Interactome: An Ecological Chronometer of Health?

An increasing number of studies reveal that host-microbial interactome networks are coordinated, impacting human health and disease. Recently, several lines of evidence have revealed associations between the acquisition of a complex microbiota and adaptive immunity, supporting that host-microbiota symbiotic relationships have evolved as a means to maintain homeostasis where the role of the microbiota is to promote and educate the immune system. Here, we hypothesize an oral host-microbial interactome that could serve as an ecological chronometer of health and disease, with specific focus on caries, periodontal diseases, and cancer. We also review the current state of the art on the human oral microbiome and its correlations with host innate immunity, and host cytokine control, with the goal of using this information for disease prediction and designing novel treatments for local and systemic dysbiosis. In addition, we discuss new insights into the role of novel host-microbial signals as potential biomarkers, and their relevance for the future of precision dentistry and medicine.