Amino acid composition and amino acid-metabolic network in supragingival plaque

Multiomics analysis reveals the genetic and metabolic characteristics associated with the low prevalence of dental caries

Background

Despite poor oral hygiene, the Baiku Yao (BKY) ethnic group in China presents a low prevalence of dental caries, which may be related to genetic susceptibility. Due to strict intra-ethnic marriage rule, this ethnic has an advantage in studying the interaction between genetic factors and other regulatory factors related to dental caries.

Methods

Peripheral blood from a caries-free adult male was used for whole genome sequencing, and the BKY assembled genome was compared to the Han Chinese genome. Oral saliva samples were collected from 51 subjects for metabolomic and metagenomic analysis. Multiomics data were integrated for combined analysis using bioinformatics approaches.

Results

Comparative genomic analysis revealed the presence of structural variations in several genes associated with dental caries. Metabolomic and metagenomic sequencing demonstrated the caries-free group had significantly higher concentration of antimicrobials and higher abundance of core oral health-related microbiota. The functional analysis indicated that cationic antimicrobial peptide resistance and the lipopolysaccharide biosynthesis pathway were enriched in the caries-free group.

Conclusions

Our study provided new insights into the specific regulatory mechanisms that contribute to the low prevalence of dental caries in the specific population and may provide new evidence for the genetic diagnosis and control of dental caries.

Identification of a Biomarker Panel for Diagnosis of Early Childhood Caries Using Salivary Metabolic Profile

Several studies have demonstrated that nuclear magnetic resonance (NMR) metabolic profiles can differentiate patients with caries from healthy individuals; however, these studies only identified individual metabolites. The present study aimed to identify a salivary metabolite biomarker panel for the diagnosis of early childhood caries (ECC). Saliva samples from children with and without caries were analyzed using NMR spectroscopy. Multivariate and univariate analyses were performed to identify the discriminating metabolites. Selected metabolites were further evaluated and used to detect ECC. The saliva samples of children with ECC were characterized based on the increased levels of formate, glycerophosphocholine, and lactate and reduced levels of alanine, glycine, isoleucine, lysine, proline, and tyrosine. The levels of these metabolites were significantly different from those in the control in the ECC subgroup according to caries severity and correlated with the number of decayed and filled teeth or surfaces. Subsequently, an optimal salivary metabolite biomarker panel comprising formate, lactate, proline, and glycine was developed. This panel exhibited a better diagnostic performance for ECC than a single metabolite. These results demonstrate that salivary metabolic signatures can reflect oral conditions associated with dental caries, thereby emphasizing the importance of distinct salivary metabolic profiles as potential biomarkers of ECC.

Prediction and validation of microbial community function from normal pulp to pulpitis caused by deep dentinal caries

INTRODUCTION

Microbial function changes may be responsible for dental pulp transformation from normal to diseased. However, studies on the prediction and verification of the function of the microbial community in the deep dentine and pulp of caries-induced pulpitis are lacking.

METHODS

This study included 171 cases of deep dentinal caries divided into normal pulp (NP), reversible pulpitis (RP), and irreversible pulpitis (IRP). In Experiment I, the microbial community composition was identified in 111 samples using 16S ribosomal DNA. Function prediction was performed through phylogenetic investigation of communities by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States prediction and qPCR. In Experiment II, different microbiome functions were confirmed in 60 samples using liquid chromatography-tandem mass spectrometry.

RESULTS

In Experiment I, microbial abundance significantly differed in the IRP group compared to the other two groups. The RP and NP groups had the same microbiome composition, but the predicted functional difference between the RP and NP groups pertained to membrane transport (p < .010). The predicted functional difference between the IRP and NP groups pertained to amino-acid, co-factor, and vitamin metabolism (p < .010). In Experiment II, Kyoto Encyclopedia of Genes and Genomes functional annotation revealed that the differential metabolites between the RP and NP groups did not participate in membrane transport; however, the differential metabolites between the IRP and NP groups participated in amino-acid metabolism.

CONCLUSIONS

The near-pulp microbiome in RP and NP with deep dentinal caries had the same differential function. However, amino acid metabolism in near the pulp microbial community differed between IRP and NP with deep dentinal caries.

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.

Metataxonomic and metabolomic evidence of biofilm homeostasis disruption related to caries: an in vitro study

The ecological dysbiosis of a biofilm includes not only bacterial changes but also changes in their metabolism. Related to oral biofilms, changes in metabolic activity are crucial endpoint, linked directly to the pathogenicity of oral diseases. Despite the advances in caries research, detailed microbial and metabolomic etiology is yet to be fully clarified. To advance this knowledge, a meta‐taxonomic approach based on 16S rRNA gene sequencing and an untargeted metabolomic approach based on an ultra‐high performance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry analysis (UHPLC/Q‐TOF‐MS) were conducted. To this end, an in vitro biofilm model derived from the saliva of healthy participants were developed, under commensal and cariogenic conditions by adding sucrose as the disease trigger. The cariogenic biofilms showed a significant increase of Firmicutes phyla (p = 0.019), due to the significant increase in the genus Streptococcus (p = 0.010), and Fusobacter (p < 0.001), by increase Fusobacterium (p < 0.001) and Sphingomonas (p = 0.024), while suffered a decrease in Actinobacteria (p < 0.001). As a consequence of the shift in microbiota composition, significant extracellular metabolomics changes were detected, showed 59 metabolites of the 120 identified significantly different in terms of relative abundance between the cariogenic/commensal biofilms (Rate of change > 2 and FDR < 0.05). Forty‐two metabolites were significantly higher in abundance in the cariogenic biofilms, whereas 17 metabolites were associated significantly with the commensal biofilms, principally related protein metabolism, with peptides and amino acids as protagonists, latter represented by histidine, arginine, l‐methionine, glutamic acid, and phenylalanine derivatives.

Application of Machine Learning Methods in Predicting Nuclear Receptors and their Families

Nuclear receptors (NRs) are a superfamily of ligand-dependent transcription factors that are closely related to cell development, differentiation, reproduction, homeostasis, and metabolism. According to the alignments of the conserved domains, NRs are classified and assigned the following seven subfamilies or eight subfamilies: (1) NR1: thyroid hormone like (thyroid hormone, retinoic acid, RAR-related orphan receptor, peroxisome proliferator activated, vitamin D3- like), (2) NR2: HNF4-like (hepatocyte nuclear factor 4, retinoic acid X, tailless-like, COUP-TFlike, USP), (3) NR3: estrogen-like (estrogen, estrogen-related, glucocorticoid-like), (4) NR4: nerve growth factor IB-like (NGFI-B-like), (5) NR5: fushi tarazu-F1 like (fushi tarazu-F1 like), (6) NR6: germ cell nuclear factor like (germ cell nuclear factor), and (7) NR0: knirps like (knirps, knirpsrelated, embryonic gonad protein, ODR7, trithorax) and DAX like (DAX, SHP), or dividing NR0 into (7) NR7: knirps like and (8) NR8: DAX like. Different NRs families have different structural features and functions. Since the function of a NR is closely correlated with which subfamily it belongs to, it is highly desirable to identify NRs and their subfamilies rapidly and effectively. The knowledge acquired is essential for a proper understanding of normal and abnormal cellular mechanisms. With the advent of the post-genomics era, huge amounts of sequence-known proteins have increased explosively. Conventional methods for accurately classifying the family of NRs are experimental means with high cost and low efficiency. Therefore, it has created a greater need for bioinformatics tools to effectively recognize NRs and their subfamilies for the purpose of understanding their biological function. In this review, we summarized the application of machine learning methods in the prediction of NRs from different aspects. We hope that this review will provide a reference for further research on the classification of NRs and their families.

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.

Carbon source utilization patterns in dental plaque and microbial responses to sucrose, lactose, and phenylalanine consumption in severe early childhood caries

Background

Severe early childhood caries (S-ECC) is mainly caused by the interaction of microbiota and environmental factors. However, the metabolic profiles of S-ECC microbial communities and the community-level microbial responses to carbohydrates and amino acids are poorly understood.

Methods

We collected supragingival plaques from 15 caries-free (CF) and 14 S-ECC children. Cultivation on Biolog AN microplates together with next-generation sequencing was used to analyze sole carbon source utilization patterns and microbial responses to sucrose, lactose and phenylalanine.

Results

S-ECC plaques had greater overall metabolic activity than those of CF ones. Comparing with CF, S-ECC plaques utilized more sucrose and lactose but less phenylalanine and then had greater response to carbohydrates. A remarkable increase of non-mutans Streptococci was observed in sucrose and lactose consumption. Lactose led to less differently distributed taxa than sucrose in both CF and S-ECC groups. Sucrose made the originally different S-ECC and CF communities eventually became similar to each other, but they remained dissimilar in lactose.

Conclusion

S-ECC plaques had more active interaction with cariogenic carbohydrates like sucrose and lactose than healthy plaques. We supported lactose has less cariogenicity compared with sucrose from microbial community structural aspect. Phenylalanine may have a potentially inhibitory effect on caries development.

Metabolic Profile of Supragingival Plaque Exposed to Arginine and Fluoride

Caries lesions develop when acid production from bacterial metabolism of dietary carbohydrates outweighs the various mechanisms that promote pH homeostasis, including bacterial alkali production. Therapies that provide arginine as a substrate for alkali production in supragingival oral biofilms have strong anticaries potential. The objective of this study was to investigate the metabolic profile of site-specific supragingival plaque in response to the use of arginine (Arg: 1.5% arginine, fluoride-free) or fluoride (F: 1,100 ppm F/NaF) toothpastes. Eighty-three adults of different caries status were recruited and assigned to treatment with Arg or F for 12 wk. Caries lesions were diagnosed using International Caries Detection and Assessment System II, and plaque samples were collected from caries-free and carious tooth surfaces. Taxonomic profiles were obtained by HOMINGS (Human Oral Microbe Identification using Next Generation Sequencing), and plaque metabolism was assessed by the levels of arginine catabolism via the arginine deiminase pathway (ADS), acidogenicity, and global metabolomics. Principal component analysis (PCA), partial least squares-discriminant analysis, analysis of variance, and random forest tests were used to distinguish metabolic profiles. Of the 509 active lesions diagnosed at baseline, 70 (14%) were inactive after 12 wk. Generalized linear model showed that enamel lesions were significantly more likely to become inactive compared to dentin lesions (P < 0.0001), but no difference was found when treatment with Arg was compared to F (P = 0.46). Arg significantly increased plaque ADS activity (P = 0.031) and plaque pH values after incubation with glucose (P = 0.001). F reduced plaque lactate production from endogenous sources (P = 0.02). PCA revealed differences between the metabolic profiles of plaque treated with Arg or F. Arg significantly affected the concentrations of 16 metabolites, including phenethylamine, agmatine, and glucosamine-6-phosphate (P < 0.05), while F affected the concentrations of 9 metabolites, including phenethylamine, N-methyl-glutamate, and agmatine (P < 0.05). The anticaries mechanisms of action of arginine and fluoride are distinct. Arginine metabolism promotes biofilm pH homeostasis, whereas fluoride is thought to enhance resistance of tooth minerals to low pH and reduce acid production by supragingival oral biofilms.

Distinctions and associations between the microbiota of saliva and supragingival plaque of permanent and deciduous teeth

BACKGROUND

Using salivary microbiota as an accurate proxy for monitoring supragingival microbiota remains controversial because their relationship remains unclear. The eruption of permanent teeth and the exfoliation of primary teeth in mixed dentition greatly alter microbial habitats, which may cause compositional shifts of oral microbiota from childhood to adults.

OBJECTIVE

This study's purpose was to assess whether saliva represents a suitable sample for monitoring supragingival microbiota in healthy people, and to explore how the replacement process of deciduous teeth with permanent teeth in mixed dentition influences microbiota within the oral cavity.

DESIGN

Samples of saliva and of supragingival plaque from permanent and deciduous teeth were collected separately from 20 healthy children with mixed dentition. To characterize their microbial communities, we used the V3-V4 hypervariable region of the bacterial 16S rRNA gene sequence.

RESULTS

Saliva harbored a less even and less diverse community than did the plaque. Discriminating genera, namely Rothia and Streptococcus, contributed to the saliva and plaque differentiation. About half of predicted KEGG pathways varied between the plaque and saliva communities. Oral bacteria showed significantly associations between their supragingival and salivary states. We identified 20 supragingival plaque-related genera in saliva, such as Corynebacterium, Capnocytophaga, Fusobacterium, and Neisseria. Additionally, the relative abundance of Actinobacteria peaked in the permanent teeth plaque but subsided in deciduous teeth plaque and saliva. The exfoliation of deciduous teeth and eruption of permanent teeth might be related to the reported fluctuation in the relative abundance of Actinobacteria from primary dentition to permanent dentition within the oral cavity. The variation between PT and DT was due mainly to permanent teeth being enriched in Actinomyces and deciduous teeth in Treponema.

CONCLUSION

These results suggested that the supragingival plaque-related bacteria could be suitable candidates when sampling saliva for monitoring supragingival microbiota. The replacement process of deciduous teeth with permanent teeth in mixed dentition might be related to the reported age-maturation of phylum Actinobacteria in the oral cavity.

High-resolution microbiome profiling uncovers Fusobacterium nucleatum, Lactobacillus gasseri/johnsonii, and Lactobacillus vaginalis associated to oral and oropharyngeal cancer in saliva from HPV positive and HPV negative patients treated with surgery and chemo-radiation

Microbiome studies show altered microbiota in head and neck squamous cell carcinoma (HNSCC), both in terms of taxonomic composition and metabolic capacity. These studies utilized a traditional bioinformatics methodology, which allows for accurate taxonomic assignment down to the genus level, but cannot accurately resolve species level membership. We applied Resphera Insight, a high-resolution methodology for 16S rRNA taxonomic assignment that is able to provide species-level context in its assignments of 16S rRNA next generation sequencing (NGS) data.

Resphera Insight applied to saliva samples from HNSCC patients and healthy controls led to the discovery that a subset of HNSCC saliva samples is significantly enriched with commensal species from the vaginal flora, including Lactobacillus gasseri/johnsonii (710x higher in saliva) and Lactobacillus vaginalis (52x higher in saliva). These species were not observed in normal saliva from Johns Hopkins patients, nor in 16S rRNA NGS saliva samples from the Human Microbiome Project (HMP). Interestingly, both species were only observed in saliva from Human Papilloma Virus (HPV) positive and HPV negative oropharyngeal cancer patients. We confirmed the representation of both species in HMP data obtained from mid-vagina (n=128) and vaginal introitus (n=121) samples.

Resphera Insight also led to the discovery that Fusobacterium nucleatum, an oral cavity flora commensal bacterium linked to colon cancer, is enriched (600x higher) in saliva from a subset of HNSCC patients with advanced tumors stages.

Together, these high-resolution analyses on 583 samples suggest a possible role for bacterial species in the therapeutic outcome of HPV positive and HPV negative HNSCC patients.

Second Era of OMICS in Caries Research: Moving Past the Phase of Disillusionment

Novel approaches using OMICS techniques enable a collective assessment of multiple related biological units, including genes, gene expression, proteins, and metabolites. In the past decade, next-generation sequencing ( NGS) technologies were improved by longer sequence reads and the development of genome databases and user-friendly pipelines for data analysis, all accessible at lower cost. This has generated an outburst of high-throughput data. The application of OMICS has provided more depth to existing hypotheses as well as new insights in the etiology of dental caries. For example, the determination of complete bacterial microbiomes of oral samples rather than selected species, together with oral metatranscriptome and metabolome analyses, supports the viewpoint of dysbiosis of the supragingival biofilms. In addition, metabolome studies have been instrumental in disclosing the contributions of major pathways for central carbon and amino acid metabolisms to biofilm pH homeostasis. New, often noncultured, oral streptococci have been identified, and their phenotypic characterization has revealed candidates for probiotic therapy. Although findings from OMICS research have been greatly informative, problems related to study design, data quality, integration, and reproducibility still need to be addressed. Also, the emergence and continuous updates of these computationally demanding technologies require expertise in advanced bioinformatics for reliable interpretation of data. Despite the obstacles cited above, OMICS research is expected to encourage the discovery of novel caries biomarkers and the development of next-generation diagnostics and therapies for caries control. These observations apply equally to the study of other oral diseases.