Metabolic Fingerprints from the Human Oral Microbiome Reveal a Vast Knowledge Gap of Secreted Small Peptidic Molecules

The Evolving Microbiome of Dental Caries

Dental caries is a significant oral and public health problem worldwide, especially in low-income populations. The risk of dental caries increases with frequent intake of dietary carbohydrates, including sugars, leading to increased acidity and disruption of the symbiotic diverse and complex microbial community of health. Excess acid production leads to a dysbiotic shift in the bacterial biofilm composition, demineralization of tooth structure, and cavities. Highly acidic and acid-tolerant species associated with caries include Streptococcus mutans, Lactobacillus, Actinomyces, Bifidobacterium, and Scardovia species. The differences in microbiotas depend on tooth site, extent of carious lesions, and rate of disease progression. Metagenomics and metatranscriptomics not only reveal the structure and genetic potential of the caries-associated microbiome, but, more importantly, capture the genetic makeup of the metabolically active microbiome in lesion sites. Due to its multifactorial nature, caries has been difficult to prevent. The use of topical fluoride has had a significant impact on reducing caries in clinical settings, but the approach is costly; the results are less sustainable for high-caries-risk individuals, especially children. Developing treatment regimens that specifically target S. mutans and other acidogenic bacteria, such as using nanoparticles, show promise in altering the cariogenic microbiome, thereby combatting the disease.

The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples

Metabolomics by gas chromatography/mass spectrometry (GC/MS) provides a standardized and reliable platform for understanding small molecule biology. Since 2005, the West Coast Metabolomics Center at the University of California at Davis has collated GC/MS metabolomics data from over 156,000 samples and 2000 studies into the standardized BinBase database. We believe that the observations from these samples will provide meaningful insight to biologists and that our data treatment and webtool will provide insight to others who seek to standardize disparate metabolomics studies. We here developed an easy-to-use query interface, BinDiscover, to enable intuitive, rapid hypothesis generation for biologists based on these metabolomic samples. BinDiscover creates observation summaries and graphics across a broad range of species, organs, diseases, and compounds. Throughout the components of BinDiscover, we emphasize the use of ontologies to aggregate large groups of samples based on the proximity of their metadata within these ontologies. This adjacency allows for the simultaneous exploration of entire categories such as "rodents", "digestive tract", or "amino acids". The ontologies are particularly relevant for BinDiscover's ontologically grouped differential analysis, which, like other components of BinDiscover, creates clear graphs and summary statistics across compounds and biological metadata. We exemplify BinDiscover's extensive applicability in three showcases across biological domains.

Illuminating the oral microbiome and its host interactions: tools and approaches for molecular ecological studies

A more comprehensive understanding of oral diseases like caries and periodontitis is dependent on an intimate understanding of the microbial ecological processes that are responsible for disease development. With this review, we provide a comprehensive overview of relevant molecular ecology techniques that have played critical roles in the current understanding of human oral biofilm development, interspecies interactions, and microbiome biogeography. The primary focus is on relevant technologies and examples available in the oral microbiology literature. However, most, if not all, of the described technologies should be readily adaptable for studies of microbiomes from other mucosal sites in the body. Therefore, this review is intended to serve as a reference guide used by microbiome researchers as they inevitably transition into molecular mechanistic studies of the many significant phenotypes observed clinically.

Investigation on the Pathological Mechanism of Frequent Exacerbators With Chronic Obstructive Pulmonary Disease Based on the Characteristics of Respiratory Flora

Chronic obstructive pulmonary disease (COPD) is a common obstructive respiratory disease characterized by persistent respiratory symptoms and limited airflow due to airway obstruction. The present study investigates the distribution characteristics of respiratory tract flora in both frequent and infrequent exacerbators of COPD. The 16S sequencing technique was adopted to differentiate the inherent differences of respiratory tract flora between frequent exacerbators and infrequent exacerbators. Additionally, cell counting kit 8 (CCK8), lactate dehydrogenase (LDH) test, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and western blot were carried out in human bronchial epithelial cells cultured in vitro and the regulatory effects of differential flora were verified. The results revealed that the observed species index, Chao1 index, and the ACE estimator of COPD frequent exacerbators were markedly higher than those of COPD infrequent exacerbators. The top five strains of COPD frequent exacerbators included g_Streptococcus (15.565%), g_Prevotella (10.683%), g_Veillonella (6.980%), g_Haemophilus (5.601%), and g_Neisseria (4.631%). Veillonella parvula generated obvious cytotoxicity and substantially reduced the activity of human bronchial epithelial cells (p < 0.01). Furthermore, the results of flow cytometry indicated that the proportion of human bronchial epithelial cells in both the S phase and G2 phase decreased following Veillonella parvula treatment indicated that Veillonella parvula inhibited cell proliferation. Meanwhile, being treated using Veillonella parvula, the expressions of interleukin-1 (IL-1), IL-6, Tumor Necrosis Factor α (TNF-α), and p-nuclear factor kappa B (NF-κB) of the cells were increased markedly (p < 0.01). Taken together, the current research demonstrated that the relative abundance of Veillonella in COPD frequent exacerbators was higher than that of infrequent exacerbators. Veillonella parvula activated the inflammatory pathway, ultimately destroyed the cell viability, and greatly impaired the activity of human bronchial epithelial cells, thereby inhibiting cell proliferation.

BiG-MAP: an Automated Pipeline To Profile Metabolic Gene Cluster Abundance and Expression in Microbiomes

Microbial gene clusters encoding the biosynthesis of primary and secondary metabolites play key roles in shaping microbial ecosystems and driving microbiome-associated phenotypes. Although effective approaches exist to evaluate the metabolic potential of such bacteria through identification of these metabolic gene clusters in their genomes, no automated pipelines exist to profile the abundance and expression levels of such gene clusters in microbiome samples to generate hypotheses about their functional roles, and to find associations with phenotypes of interest. Here, we describe BiG-MAP, a bioinformatic tool to profile abundance and expression levels of gene clusters across metagenomic and metatranscriptomic data and evaluate their differential abundance and expression under different conditions. To illustrate its usefulness, we analyzed 96 metagenomic samples from healthy and caries-associated human oral microbiome samples and identified 252 gene clusters, including unreported ones, that were significantly more abundant in either phenotype. Among them, we found the muc operon, a gene cluster known to be associated with tooth decay. Additionally, we found a putative reuterin biosynthetic gene cluster from a Streptococcus strain to be enriched but not exclusively found in healthy samples; metabolomic data from the same samples showed masses with fragmentation patterns consistent with (poly)acrolein, which is known to spontaneously form from the products of the reuterin pathway and has been previously shown to inhibit pathogenic Streptococcus mutans strains. Thus, we show how BiG-MAP can be used to generate new hypotheses on potential drivers of microbiome-associated phenotypes and prioritize the experimental characterization of relevant gene clusters that may mediate them. IMPORTANCE Microbes play an increasingly recognized role in determining host-associated phenotypes by producing small molecules that interact with other microorganisms or host cells. The production of these molecules is often encoded in syntenic genomic regions, also known as gene clusters. With the increasing numbers of (multi)omics data sets that can help in understanding complex ecosystems at a much deeper level, there is a need to create tools that can automate the process of analyzing these gene clusters across omics data sets. This report presents a new software tool called BiG-MAP, which allows assessing gene cluster abundance and expression in microbiome samples using metagenomic and metatranscriptomic data. Here, we describe the tool and its functionalities, as well as its validation using a mock community. Finally, using an oral microbiome data set, we show how it can be used to generate hypotheses regarding the functional roles of gene clusters in mediating host phenotypes.

Small molecule natural products in human nasal/oral microbiota

Small molecule natural products are a chemically diverse class of biomolecules that fulfill myriad biological functions, including autoregulation, communication with microbial neighbors and the host, interference competition, nutrient acquisition, and resistance to oxidative stress. Human commensal bacteria are increasingly recognized as a potential source of new natural products, which may provide insight into the molecular ecology of many different human body sites as well as novel scaffolds for therapeutic development. Here, we review the scientific literature on natural products derived from residents of the human nasal/oral cavity, discuss their discovery, biosynthesis, and ecological roles, and identify key questions in the study of these compounds.

The evolution and changing ecology of the African hominid oral microbiome

The microbiome plays key roles in human health, but little is known about its evolution. We investigate the evolutionary history of the African hominid oral microbiome by analyzing dental biofilms of humans and Neanderthals spanning the past 100,000 years and comparing them with those of chimpanzees, gorillas, and howler monkeys. We identify 10 core bacterial genera that have been maintained within the human lineage and play key biofilm structural roles. However, many remain understudied and unnamed. We find major taxonomic and functional differences between the oral microbiomes of Homo and chimpanzees but a high degree of similarity between Neanderthals and modern humans, including an apparent Homo-specific acquisition of starch digestion capability in oral streptococci, suggesting microbial coadaptation with host diet.

The oral microbiome plays key roles in human biology, health, and disease, but little is known about the global diversity, variation, or evolution of this microbial community. To better understand the evolution and changing ecology of the human oral microbiome, we analyzed 124 dental biofilm metagenomes from humans, including Neanderthals and Late Pleistocene to present-day modern humans, chimpanzees, and gorillas, as well as New World howler monkeys for comparison. We find that a core microbiome of primarily biofilm structural taxa has been maintained throughout African hominid evolution, and these microbial groups are also shared with howler monkeys, suggesting that they have been important oral members since before the catarrhine–platyrrhine split ca. 40 Mya. However, community structure and individual microbial phylogenies do not closely reflect host relationships, and the dental biofilms of Homo and chimpanzees are distinguished by major taxonomic and functional differences. Reconstructing oral metagenomes from up to 100 thousand years ago, we show that the microbial profiles of both Neanderthals and modern humans are highly similar, sharing functional adaptations in nutrient metabolism. These include an apparent Homo-specific acquisition of salivary amylase-binding capability by oral streptococci, suggesting microbial coadaptation with host diet. We additionally find evidence of shared genetic diversity in the oral bacteria of Neanderthal and Upper Paleolithic modern humans that is not observed in later modern human populations. Differences in the oral microbiomes of African hominids provide insights into human evolution, the ancestral state of the human microbiome, and a temporal framework for understanding microbial health and disease.

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.

Omics and interspecies interaction

Interspecies interactions are key determinants in biofilm behavior, ecology, and architecture. The cellular responses of microorganisms to each other at transcriptional, proteomic, and metabolomic levels ultimately determine the characteristics of biofilm and the corresponding implications for health and disease. Advances in omics technologies have revolutionized our understanding of microbial community composition and their activities as a whole. Large-scale analyses of the complex interaction between the many microbial species residing within a biofilm, however, are currently still hampered by technical and bioinformatics challenges. Thus, studies of interspecies interactions have largely focused on the transcriptional and proteomic changes that occur during the contact of a few prominent species, such as Porphyromonas gingivalis, Streptococcus mutans, Candida albicans, and a few others, with selected partner species. Expansion of available tools is necessary to grow the revealing, albeit limited, insight these studies have provided into a profound understanding of the nature of individual microbial responses to the presence of others. This will allow us to answer important questions including: Which intermicrobial interactions orchestrate the myriad of cooperative, synergistic, antagonistic, manipulative, and other types of relationships and activities in the complex biofilm environment, and what are the implications for oral health and disease?

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

Multi-omics tools for studying microbial biofilms: current perspectives and future directions

The advent of omics technologies has greatly improved our understanding of microbial biology, particularly in the last two decades. The field of microbial biofilms is, however, relatively new, consolidated in the 1980s. The morphogenic switching by microbes from planktonic to biofilm phenotype confers numerous survival advantages such as resistance to desiccation, antibiotics, biocides, ultraviolet radiation, and host immune responses, thereby complicating treatment strategies for pathogenic microorganisms. Hence, understanding the mechanisms governing the biofilm phenotype can result in efficient treatment strategies directed specifically against molecular markers mediating this process. The application of omics technologies for studying microbial biofilms is relatively less explored and holds great promise in furthering our understanding of biofilm biology. In this review, we provide an overview of the application of omics tools such as transcriptomics, proteomics, and metabolomics as well as multi-omics approaches for studying microbial biofilms in the current literature. We also highlight how the use of omics tools directed at various stages of the biological information flow, from genes to metabolites, can be integrated via multi-omics platforms to provide a holistic view of biofilm biology. Following this, we propose a future artificial intelligence-based multi-omics platform that can predict the pathways associated with different biofilm phenotypes.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

Computational Modeling of the Human Microbiome

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

Metabolic phenotyping of the human microbiome

The human microbiome has been identified as having a key role in health and numerous diseases. Trillions of microbial cells and viral particles comprise the microbiome, each representing modifiable working elements of an intricate bioactive ecosystem. The significance of the human microbiome as it relates to human biology has progressed through culture-dependent (for example, media-based methods) and, more recently, molecular (for example, genetic sequencing and metabolomic analysis) techniques. The latter have become increasingly popular and evolved from being used for taxonomic identification of microbiota to elucidation of functional capacity (sequencing) and metabolic activity (metabolomics). This review summarises key elements of the human microbiome and its metabolic capabilities within the context of health and disease.

Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome

The gut microbiome has been shown to play a significant role in human healthy and diseased states. The dynamic signaling that occurs between the host and microbiome is critical for the maintenance of host homeostasis. Analyzing the human microbiome with metaproteomics, metabolomics, and integrative multi-omics analyses can provide significant information on markers for healthy and diseased states, allowing for the eventual creation of microbiome-targeted treatments for diseases associated with dysbiosis. Metaproteomics enables functional activity information to be gained from the microbiome samples, while metabolomics provides insight into the overall metabolic states affecting/representing the host-microbiome interactions. Combining these functional -omic platforms together with microbiome composition profiling allows for a holistic overview on the functional and metabolic state of the microbiome and its influence on human health. Here the benefits of metaproteomics, metabolomics, and the integrative multi-omic approaches to investigating the gut microbiome in the context of human health and diseases are reviewed.

Expanding the Vocabulary of Peptide Signals in Streptococcus mutans

Streptococci, including the dental pathogen Streptococcus mutans, undergo cell-to-cell signaling that is mediated by small peptides to control critical physiological functions such as adaptation to the environment, control of subpopulation behaviors and regulation of virulence factors. One such model pathway is the regulation of genetic competence, controlled by the ComRS signaling system and the peptide XIP. However, recent research in the characterization of this pathway has uncovered novel operons and peptides that are intertwined into its regulation. These discoveries, such as cell lysis playing a critical role in XIP release and importance of bacterial self-sensing during the signaling process, have caused us to reevaluate previous paradigms and shift our views on the true purpose of these signaling systems. The finding of new peptides such as the ComRS inhibitor XrpA and the peptides of the RcrRPQ operon also suggests there may be more peptides hidden in the genomes of streptococci that could play critical roles in the physiology of these organisms. In this review, we summarize the recent findings in S. mutans regarding the integration of other circuits into the ComRS signaling pathway, the true mode of XIP export, and how the RcrRPQ operon controls competence activation. We also look at how new technologies can be used to re-annotate the genome to find new open reading frames that encode peptide signals. Together, this summary of research will allow us to reconsider how we perceive these systems to behave and lead us to expand our vocabulary of peptide signals within the genus Streptococcus.

Diversity and functional analysis of salivary microflora of Indian Antarctic expeditionaries

Introduction: The human oral microbiota continues to change phenotype by many factors (environment, diet, genetics, stress, etc.), throughout life with a major impact on human physiology, psychology, metabolism and immune system. Amongst one such factor with unique and extreme environmental conditions is Antarctica. The sea voyage to Antarctica has many risks than at station for expedition members. In this study, we investigated the influence of Antarctic sea voyage and stay at the Indian Antarctic station Maitri, on the health of Indian expedition members by using a metagenomic approach to explore oral biodiversity. Methods: Saliva samples were collected from 12 expedition members, at 3 different time points viz. before the start of the ship voyage, after the completion of the voyage and at the end of the stay at Antarctica. Samples were analyzed for whole genome and 16S rRNA sequencing. Result: The oral microbial diversity of the expedition members was significantly changed, during the days of sailing and after the stay at Antarctica. The oral microbiota comprised mainly of the phyla Firmicutes (46%, 29% & 36%); Proteobacteria (40%, 48%, & 44%), Bacteroidetes (10%, 22%, &14%), Fusobacterium and Actinobacteria (5%-1%) and Unclassified (17%, 25% & 23%), at three time points, respectively. Further, the differential analysis of microbes across all the phyla revealed 89, 157 and 157 OTUs genera. The altered microbiota indicated changes in amino acid, lipid and carbohydrate metabolism. Conclusion: Study suggests that understanding the compositional and functional differences in the oral microbiota of Antarctic expedition members, can lay the foundation to relate these differences to their health status. It will further demonstrate the need for providing improved management during ship voyage and stay in Antarctica.

Uncovering complex microbiome activities via metatranscriptomics during 24 hours of oral biofilm assembly and maturation

BACKGROUND

Dental plaque is composed of hundreds of bacterial taxonomic units and represents one of the most diverse and stable microbial ecosystems associated with the human body. Taxonomic composition and functional capacity of mature plaque is gradually shaped during several stages of community assembly via processes such as co-aggregation, competition for space and resources, and by bacterially produced reactive agents. Knowledge on the dynamics of assembly within complex communities is very limited and derives mainly from studies composed of a limited number of bacterial species. To fill current knowledge gaps, we applied parallel metagenomic and metatranscriptomic analyses during assembly and maturation of an in vitro oral biofilm. This model system has previously demonstrated remarkable reproducibility in taxonomic composition across replicate samples during maturation.

RESULTS

Time course analysis of the biofilm maturation was performed by parallel sampling every 2-3 h for 24 h for both DNA and RNA. Metagenomic analyses revealed that community taxonomy changed most dramatically between three and six hours of growth when pH dropped from 6.5 to 5.5. By applying comparative metatranscriptome analysis we could identify major shifts in overall community activities between six and nine hours of growth when pH dropped below 5.5, as 29,015 genes were significantly up- or down- expressed. Several of the differentially expressed genes showed unique activities for individual bacterial genomes and were associated with pyruvate and lactate metabolism, two-component signaling pathways, production of antibacterial molecules, iron sequestration, pH neutralization, protein hydrolysis, and surface attachment. Our analysis also revealed several mechanisms responsible for the niche expansion of the cariogenic pathogen Lactobacillus fermentum.

CONCLUSION

It is highly regarded that acidic conditions in dental plaque cause a net loss of enamel from teeth. Here, as pH drops below 5.5 pH to 4.7, we observe blooms of cariogenic lactobacilli, and a transition point of many bacterial gene expression activities within the community. To our knowledge, this represents the first study of the assembly and maturation of a complex oral bacterial biofilm community that addresses gene level functional responses over time.

Live and let die: Hydrogen peroxide production by the commensal flora and its role in maintaining a symbiotic microbiome

The majority of commensal oral streptococci are able to generate hydrogen peroxide (H₂ O₂ ) during aerobic growth, which can diffuse through the cell membrane and inhibit competing species in close proximity. Competing H₂ O₂ production is mainly dependent upon the pyruvate oxidase SpxB, and to a lesser extent the lactate oxidase LctO, both of which are important for energy generation in aerobic environments. Several studies point to a broad impact of H₂ O₂ production in the oral environment, including a potential role in biofilm homeostasis, signaling, and interspecies interactions. Here, we summarize the current research regarding oral streptococcal H₂ O₂ generation, resistance mechanisms, and the ecological impact of H₂ O₂ production. We also discuss the potential therapeutic utility of H₂ O₂ for the prevention/treatment of dysbiotic diseases as well as its potential role as a biomarker of oral health.

Consistent and reproducible long-term in vitro growth of health and disease-associated oral subgingival biofilms

BACKGROUND

Several in vitro oral biofilm growth systems can reliably construct oral microbiome communities in culture, yet their stability and reproducibility through time has not been well characterized. Long-term in vitro growth of natural biofilms would enable use of these biofilms in both in vitro and in vivo studies that require complex microbial communities with minimal variation over a period of time. Understanding biofilm community dynamics in continuous culture, and whether they maintain distinct signatures of health and disease, is necessary to determine the reliability and applicability of such models to broader studies. To this end, we performed next-generation sequencing on biofilms grown from healthy and disease-site subgingival plaque for 80 days to assess stability and reliability of continuous oral biofilm growth.

RESULTS

Biofilms were grown from subgingival plaque collected from periodontitis-affected sites and healthy individuals for ten eight-day long generations, using hydroxyapatite disks. The bacterial community in each generation was determined using Human Oral Microbe Identification by Next-Generation Sequencing (HOMINGS) technology, and analyzed in QIIME. Profiles were steady through the ten generations, as determined by species abundance and prevalence, Spearman's correlation coefficient, and Faith's phylogenetic distance, with slight variation predominantly in low abundance species. Community profiles were distinct between healthy and disease site-derived biofilms as demonstrated by weighted UniFrac distance throughout the ten generations. Differentially abundant species between healthy and disease site-derived biofilms were consistent throughout the generations.

CONCLUSIONS

Healthy and disease site-derived biofilms can reliably maintain consistent communities through ten generations of in vitro growth. These communities maintain signatures of health and disease and of individual donors despite culture in identical environments. This subgingival oral biofilm growth and perpetuation model may prove useful to studies involving oral infection or cell stimulation, or those measuring microbial interactions, which require the same biofilms over a period of time.

The Oral Microbiome Bank of China

The human microbiome project (HMP) promoted further understanding of human oral microbes. However, research on the human oral microbiota has not made as much progress as research on the gut microbiota. Currently, the causal relationship between the oral microbiota and oral diseases remains unclear, and little is known about the link between the oral microbiota and human systemic diseases. To further understand the contribution of the oral microbiota in oral diseases and systemic diseases, a Human Oral Microbiome Database (HOMD) was established in the US. The HOMD includes 619 taxa in 13 phyla, and most of the microorganisms are from American populations. Due to individual differences in the microbiome, the HOMD does not reflect the Chinese oral microbial status. Herein, we established a new oral microbiome database—the Oral Microbiome Bank of China (OMBC, http://www.sklod.org/ombc). Currently, the OMBC includes information on 289 bacterial strains and 720 clinical samples from the Chinese population, along with lab and clinical information. The OMBC is the first curated description of a Chinese-associated microbiome; it provides tools for use in investigating the role of the oral microbiome in health and diseases, and will give the community abundant data and strain information for future oral microbial studies.

A new resource for consolidating oral microbiome data will help researchers explore the relationship between these commensal communities and the health of their hosts. Numerous studies have highlighted apparent connections between alterations in the microbial communities within the human mouth and medical conditions including diabetes and cancer. A recent article from researchers led by Liao Ga at Sichuan University describes the launch of the Oral Microbiome Bank of China, an effort to study such connections by profiling specimens from individuals from across the country. The database currently houses detailed information on 289 bacterial strains and the samples from which they were obtained. The authors are now looking to analyze these data to gain insights into the structure and function of oral ecosystems, and to further expand this database as a resource for Chinese microbiome research.