Distinct signatures of dental plaque metabolic byproducts dictated by periodontal inflammatory status

Periodontal tissue susceptibility to glycaemic control in type 2 diabetes

AIM

To assess the direct effect of intensive glycaemic control on periodontal tissues in patients with diabetes mellitus.

MATERIALS AND METHODS

Twenty-nine patients with type 2 diabetes were enrolled and hospitalized to receive a 2-week intensive glycaemic control regimen. We observed and analysed the systemic and oral disease indicators before and after treatment and clarified the indicators related to periodontal inflammation.

RESULTS

A significant reduction in glycaemic and periodontal parameters, including glycated albumin levels and periodontal inflamed surface area (PISA), was observed after treatment. The changes in PISA per tooth, indicative of periodontal healing, exhibited a bimodal distribution; the patients were divided into two groups on this basis. Correlations were observed between the changes in PISA per tooth and fasting plasma glucose, acetoacetic acid, and beta-hydroxybutyrate levels in the PISA-improved group. Significantly lower levels of C-peptide, coefficient of variation of R-R interval, and ankle-brachial pressure index were observed before treatment in the PISA non-improved group.

CONCLUSIONS

Glycaemic control treatment can effectively improve periodontitis in patients with type 2 diabetes, even in the absence of specific periodontal treatments. However, the periodontal responsiveness to glycaemic control treatment depends on the systemic condition of the patient.

Effect of chronic alcohol consumption on oral microbiota in rats with periodontitis

Background

The imbalance of oral microbiota can contribute to various oral disorders and potentially impact general health. Chronic alcohol consumption beyond a certain threshold has been implicated in influencing both the onset and progression of periodontitis. However, the mechanism by which chronic alcohol consumption affects periodontitis and its association with changes in the oral microbial community remains unclear.

Objective

This study used 16S rRNA gene amplicon sequencing to examine the dynamic changes in the oral microbial community of rats with periodontitis influenced by chronic alcohol consumption.

Methods

Twenty-four male Wistar rats were randomly allocated to either a periodontitis (P) or periodontitis + alcohol (PA) group. The PA group had unrestricted access to alcohol for 10 weeks, while the P group had access to water only. Four weeks later, both groups developed periodontitis. After 10 weeks, serum levels of alanine aminotransferase and aspartate aminotransferase in the rats' serum were measured. The oral swabs were obtained from rats, and 16S rRNA gene sequencing was conducted. Alveolar bone status was assessed using hematoxylin and eosin staining and micro-computed tomography.

Results

Rats in the PA group exhibited more severe periodontal tissue damage compared to those in the periodontitis group. Although oral microbial diversity remained stable, the relative abundance of certain microbial communities differed significantly between the two groups. Actinobacteriota and Desulfobacterota were more prevalent at the phylum level in the PA group. At the genus level, Cutibacterium, Tissierella, Romboutsia, Actinomyces, Lawsonella, Anaerococcus, and Clostridium_sensu_stricto_1 were significantly more abundant in the PA group, while Haemophilus was significantly less abundant. Additionally, functional prediction using Tax4Fun revealed a significant enrichment of carbohydrate metabolism in the PA group.

Conclusion

Chronic alcohol consumption exacerbated periodontitis in rats and influenced the composition and functional characteristics of their oral microbiota, as indicated by 16S rRNA gene sequencing results. These microbial alterations may contribute to the exacerbation of periodontitis in rats due to chronic alcohol consumption.

Combined assessment of lysine and N-acetyl cadaverine levels assist as a potential biomarker of the smoker periodontitis

Periodontitis is an inflammatory condition of supporting structures of teeth leading to attachment and bone loss. Cigarette smoking is the single most important and modifiable risk factor with 5 to 20-fold susceptibility for periodontal diseases. Reverse smoking is a peculiar habit of smoking where the lit end is kept inside the mouth, which is predominant in the northern coastal districts of Andhra Pradesh. Polyamines are biologically active amines involved in tissue regeneration and modulation of inflammation. The study aimed to evaluate polyamines and check their utility as a marker in detection of periodontitis among different groups. Total polyamine levels showed significant increase in reverse smokers with periodontitis when compared to the other groups. Qualitative analysis by thin layer chromatography showed three polyamine bands with varying intensity among the different groups. Mass spectrometric and NMR analyses of the three bands identified them as N1, N8-diacetyl spermidine, N-acetyl cadaverine and lysine. Most significantly elevated levels of lysine was observed in the smoker and reverse smoker periodontitis groups when compared to healthy and non-smoker periodontitis groups. The significantly elevated levels of N-acetyl cadaverine could be responsible for the more destruction of periodontium in the reverse smoker group. Antioxidant potential decreased significantly in different smoker periodontitis groups. The present study suggests that the quantitative analysis of salivary polyamines, lysine and N-acetyl cadaverine can aid as an easy noninvasive diagnostic method for assessing the periodontal status, especially in smokers.

Dental restorative materials and halitosis: a preliminaryin-vitrostudy

Despite the widespread use of dental restorative materials, little information exists in the literature regarding their potential impact on bad breath. This in vitro study aims to fill this gap by investigating the influence of different restorative materials on the release of hydrogen sulfide (H2S). Thirteen diverse dental restorative materials, including composites, flowable composites, glass ionomer restorative materials, high-copper amalgam, and CAD-CAM blocks, were examined. Cellulose Sponge models were used as negative and positive control. All samples were prepared with a diameter of 5 mm and a height of 2 mm. Except for the negative control group, all samples were embedded into Allium cepa L., and the emitted H2S was measured using the Wintact W8802 hydrogen sulfide monitor. Surface roughness's effect on emission was explored by roughening the surfaces of CAD-CAM material samples, and gas emission was measured again. The data were statistically analyzed using the Kruskal-Wallis test and DSCF pairwise comparison tests. Fiber-reinforced flowable composite (EverX Flow), amalgam (Nova 70-caps), and certain composite materials (IPS Empress Direct, Tetric Evoceram, Admira Fusion X-tra) released higher H2S concentrations compared to the negative control. The H2S release period lasted longer in the same materials mentioned above, along with G-aenial Universal Injectable. Indirectly used materials, such as GC Cerasmart, Vita Enamic, and Vita YZ HT, demonstrated significantly lower emissions compared to other direct restoratives. Importantly, the surface roughness of indirect materials did not significantly affect peak H2S concentrations or release times. The study reveals variations in H2S release among restorative materials, suggesting potential advantages of indirect restorative materials in reducing H2S-induced halitosis. This comprehensive understanding of the relationship between restorative materials and halitosis can empower both dental professionals and patients to make well-informed treatment choices. Notably, there is evidence supporting the enhanced performance of indirect restorative materials for individuals affected by halitosis.

The polymicrobial pathogenicity of Porphyromonas gingivalis

Accumulating microbiome data and mechanistic studies in vitro and in vivo have refined our understanding of the oral microbiota as a functionally integrated polymicrobial community. Emergent properties of these communities are driven to a large extent by interspecies communication which can be based on physical association, secreted small molecules or nutritional exchange. Porphyromonas gingivalis is a consensus periodontal pathogen; however, virulence is only expressed in the context of a polymicrobial community. Multivalent fimbriae mediate attachment to other oral species which can initiate a distinct transcriptional program in both constituents of the binding pair. P. gingivalis also responds to small molecules and nutritional cues produced by partner organisms. Physiological interdependence forms the basis of complex networks of cooperating organisms which begin to resemble an organismal entity exhibiting a spectrum of pathogenic potential.

Current concepts in the pathogenesis of periodontitis: from symbiosis to dysbiosis

The primary etiological agent for the initiation and progression of periodontal disease is the dental plaque biofilm which is an organized aggregation of microorganisms residing within a complex intercellular matrix. The non-specific plaque hypothesis was the first attempt to explain the role of the dental biofilm in the pathogenesis of periodontal diseases. However, the introduction of sophisticated diagnostic and laboratory assays has led to the realisation that the development of periodontitis requires more than a mere increase in the biomass of dental plaque. Indeed, multispecies biofilms exhibit complex interactions between the bacteria and the host. In addition, not all resident microorganisms within the biofilm are pathogenic, since beneficial bacteria exist that serve to maintain a symbiotic relationship between the plaque microbiome and the host’s immune-inflammatory response, preventing the emergence of pathogenic microorganisms and the development of dysbiosis. This review aims to highlight the development and structure of the dental plaque biofilm and to explore current literature on the transition from a healthy (symbiotic) to a diseased (dysbiotic) biofilm in periodontitis and the associated immune-inflammatory responses that drive periodontal tissue destruction and form mechanistic pathways that impact other systemic non-communicable diseases.

Identification of potential salivary biomarkers for Sjögren's syndrome with an untargeted metabolomic approach

INTRODUCTION

Despite the rise of metabolomics over the past years, and particularly salivary metabolomics, little research on Sjögren's syndrome (SS) biomarkers has focused on the salivary metabolome.

OBJECTIVES

This study aims to identify metabolites that could be used as biomarkers for SS.

METHODS

Using the software called XCMS online, the salivary metabolic profiles obtained with liquid chromatography coupled to high-resolution mass spectrometry for 18 female SS patients were compared to those obtained for 22 age-matched female healthy controls.

RESULTS AND CONCLUSION

A total of 91 metabolites showed differential expression in SS patients. A putative identification was proposed with the use of a database for 37 of these metabolites and, of these, 16 identifications were confirmed. Given the identified metabolites, some important metabolic pathways, such as amino acid metabolism, purine metabolism, or even the citric acid cycle seem to be affected. Through the analyses of the ROC (receiver operating characteristic) curves, three metabolites, namely alanine, isovaleric acid, and succinic acid, showed both good sensitivity (respectively 1.000, 1.000, and 0.750) and specificity (respectively 0.692, 0.615, and 0.692) for identifying SS and could then be interesting biomarkers for a potential salivary diagnosis test.

Microbial metabolites in the pathogenesis of periodontal diseases: a narrative review

The purpose of this narrative review is to highlight the importance of microbial metabolites in the pathogenesis of periodontal diseases. These diseases, involving gingivitis and periodontitis are inflammatory conditions initiated and maintained by the polymicrobial dental plaque/biofilm. Gingivitis is a reversible inflammatory condition while periodontitis involves also irreversible destruction of the periodontal tissues including the alveolar bone. The inflammatory response of the host is a natural reaction to the formation of plaque and the continuous release of metabolic waste products. The microorganisms grow in a nutritious and shielded niche in the periodontal pocket, protected from natural cleaning forces such as saliva. It is a paradox that the consequences of the enhanced inflammatory reaction also enable more slow-growing, fastidious, anaerobic bacteria, with often complex metabolic pathways, to colonize and thrive. Based on complex food chains, nutrient networks and bacterial interactions, a diverse microbial community is formed and established in the gingival pocket. This microbiota is dominated by anaerobic, often motile, Gram-negatives with proteolytic metabolism. Although this alternation in bacterial composition often is considered pathologic, it is a natural development that is promoted by ecological factors and not necessarily a true "dysbiosis". Normal commensals are adapting to the gingival crevice when tooth cleaning procedures are absent. The proteolytic metabolism is highly complex and involves a number of metabolic pathways with production of a cascade of metabolites in an unspecific manner. The metabolites involve short chain fatty acids (SCFAs; formic, acetic, propionic, butyric, and valeric acid), amines (indole, scatole, cadaverine, putrescine, spermine, spermidine) and gases (NH₃, CO, NO, H₂S, H₂). A homeostatic condition is often present between the colonizers and the host response, where continuous metabolic fluctuations are balanced by the inflammatory response. While it is well established that the effect of the dental biofilm on the host response and tissue repair is mediated by microbial metabolites, the mechanisms behind the tissue destruction (loss of clinical attachment and bone) are still poorly understood. Studies addressing the functions of the microbiota, the metabolites, and how they interplay with host tissues and cells, are therefore warranted.

Association between periodontitis and uric acid levels in blood and oral fluids: a systematic review and meta-analysis

BACKGROUND

Uric acid, a formerly-known antioxidant that has recently been linked to numerous inflammatory diseases as a pro-inflammatory and -oxidative mediator in pathological conditions. It is imperative to reassess the association between periodontitis and uric acid locally and systematically. The aim of this systematic review was to systemically evaluate the association between periodontitis and the uric acid (UA) levels in blood, saliva and gingival crevicular fluid (GCF).

METHODS

Relevant clinical studies up to January 28, 2023 were identified and retrieved from electronic databases including PubMed, Scopus, EMBASE and Web of Science, with periodontitis, uric acid, hyperuricemia and gout as the keywords. The weighted (WMD) or standardized mean difference (SMD) was calculated using fixed- or random-effect models. Methodological heterogeneity was assessed.

RESULTS

Sixteen eligible observational studies and one RCT were enrolled, which included 1354 patients with periodontitis and 989 controls. Three sample types for UA detection were involved, including blood (n = 8), saliva (n = 9) and GCF (n = 1). Meta-analysis demonstrated an enhanced plasma UA concentration (WMD = 1.00 mg/dL, 95% CI 0.63 to 1.37, P < 0.001) but a decreased salivary UA level (SMD = -0.95, 95% CI -1.23 to -0.68, P < 0.001) in periodontitis versus control. Statistical heterogeneity among the plasma- and saliva-tested studies were moderate (I² = 58.3%, P = 0.066) and low (I² = 33.8%, P = 0.196), respectively.

CONCLUSIONS

Within the limitations of the enrolled studies, it seems that there is an association between periodontitis and increased blood UA and decreased salivary UA. (Registration no. CRD42020172535 in Prospero).

Microbiome, alveolar bone, and metabolites: Connecting the dots

The oral microbiome (OM) is a diverse and dynamic collection of species, separated from alveolar bone by the oral mucosa. Pathogenic shifts in the OM (dysbiosis) during periodontitis are associated with an inflammatory response in the oral mucosa that drives alveolar bone resorption. Alveolar bone is also affected by metabolic disorders such as osteoporosis. Accumulating evidence has linked another microbial community, the gut microbiome (GM), to systemic bone metabolism and osteoporosis. Underlying this connection is the biologic activity of metabolites, byproducts of host and bacterial activity. Limited evidence also suggests that metabolites in the oral cavity signal between the OM and immune system, influencing both alveolar bone homeostasis and pathologic bone destruction in periodontitis. While the oral cavity and gut are connected through the gastrointestinal tract, dissimilar roles for known metabolites between these two niches exemplify the difficulty in translating knowledge on gut-derived metabolites and bone metabolism to alveolar bone. Integrated metabolomic, transcriptomic, and metagenomic approaches hold promise for resolving these challenges and identifying novel metabolites which impact alveolar bone health. Further interrogation through mechanistic testing in pre-clinical models and carefully controlled clinical studies have potential to lead toward translation of these discoveries into meaningful therapies.

Towards multiomic analysis of oral mucosal pathologies

Oral mucosal pathologies comprise an array of diseases with worldwide prevalence and medical relevance. Affecting a confined space with crucial physiological and social functions, oral pathologies can be mutilating and drastically reduce quality of life. Despite their relevance, treatment for these diseases is often far from curative and remains vastly understudied. While multiple factors are involved in the pathogenesis of oral mucosal pathologies, the host's immune system plays a major role in the development, maintenance, and resolution of these diseases. Consequently, a precise understanding of immunological mechanisms implicated in oral mucosal pathologies is critical (1) to identify accurate, mechanistic biomarkers of clinical outcomes; (2) to develop targeted immunotherapeutic strategies; and (3) to individualize prevention and treatment approaches. Here, we review key elements of the immune system's role in oral mucosal pathologies that hold promise to overcome limitations in current diagnostic and therapeutic approaches. We emphasize recent and ongoing multiomic and single-cell approaches that enable an integrative view of these pathophysiological processes and thereby provide unifying and clinically relevant biological signatures.

The Voltammetric Detection of Cadaverine Using a Diamine Oxidase and Multi-Walled Carbon Nanotube Functionalised Electrochemical Biosensor

Cadaverine is a biomolecule of major healthcare importance in periodontal disease; however, current detection methods remain inefficient. The development of an enzyme biosensor for the detection of cadaverine may provide a cheap, rapid, point-of-care alternative to traditional measurement techniques. This work developed a screen-printed biosensor (SPE) with a diamine oxidase (DAO) and multi-walled carbon nanotube (MWCNT) functionalised electrode which enabled the detection of cadaverine via cyclic voltammetry and differential pulse voltammetry. The MWCNTs were functionalised with DAO using carbodiimide crosslinking with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) and N-Hydroxysuccinimide (NHS), followed by direct covalent conjugation of the enzyme to amide bonds. Cyclic voltammetry results demonstrated a pair of distinct redox peaks for cadaverine with the C-MWCNT/DAO/EDC-NHS/GA SPE and no redox peaks using unmodified SPEs. Differential pulse voltammetry (DPV) was used to isolate the cadaverine oxidation peak and a linear concentration dependence was identified in the range of 3-150 µg/mL. The limit of detection of cadaverine using the C-MWCNT/DAO/EDC-NHS/GA SPE was 0.8 μg/mL, and the biosensor was also found to be effective when tested in artificial saliva which was used as a proof-of-concept model to increase the Technology Readiness Level (TRL) of this device. Thus, the development of a MWCNT based enzymatic biosensor for the voltammetric detection of cadaverine which was also active in the presence of artificial saliva was presented in this study.

Analysis of subgingival micro-organisms based on multi-omics and Treg/Th17 balance in type 2 diabetes with/without periodontitis

Type 2 diabetes mellitus (T2DM) and periodontitis are common and interrelated diseases, resulting in altered host response microbiota. The subgingival micro-organisms play a key role in periodontitis pathogenesis. To assess the shift of subgingival microbiome and metabolome in T2DM, we performed an analysis of the subgingival microbiome in patients with T2DM (n = 20) compared with non-diabetes (ND) subjects (n = 21). Furthermore, patients were subdivided into 10 T2DM with periodontitis (DP), 10 T2DM without periodontitis (DNP), 10 periodontitis (P), and 11 healthy control (H) groups. 16SrRNA gene sequencing combined with ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS) based metabolomics was performed in all participants. T lymphocyte immunity was analyzed by flow cytometry. Furthermore, the network relationship among subgingival micro-organisms, metabolites, blood glucose level, and T lymphocyte immunity were analyzed. The results showed that the difference of the subgingival microbiome from healthy to periodontitis status was less prominent in T2DM compared with ND, though the clinical signs of disease were similar. The bacteria Eubacterium nodatum group, Filifactor, Fretibacterium, Peptostreptococcus, and Desulfovibrio, amongst others, may be important in the pathopoiesia of periodontitis in the T2DM state. In addition, some dominant bacteria showed network relationships. The Treg/Th17 ratio was lower in the DP and DNP groups than in the P and H groups-though that of P was lower than for H. The percentage of CD4+/CD8+ PD1 and CD8+ PDL1 was higher in the DP and DNP groups than in the H group; the percentage of CD8+ PDL1 was higher in the DP than P groups. Subgingival micro-organisms in periodontitis had a significant metabolic shift in terms of their signature metabolites. Butyrate metabolism and phenylalanine metabolism may play a role in the pathogenesis of periodontitis with/without T2DM. Specifically, biphenyl degradation, tryptophan metabolism, and the two-component system may play important roles in periodontitis with T2DM. Lastly, the network relationship among subgingival micro-organisms, metabolites, blood glucose level, and T lymphocyte immunity were unbalanced. This study identified the changes in the subgingival microbiome associated with periodontitis in T2DM, as well as the associated network between bacterial flora, metabolism dysbiosis, and immune regulation.

Recent progress and perspectives on the relationship between hyperuricemia and periodontitis

Periodontitis is one of the most prevalent diseases in oral cavity, which could not merely lead to the destruction of supporting or surrounding tooth structures but also affect the whole-body health such as the digestive and nervous systems. Epidemiological investigations suggested that in some developed countries, more than 45% or even 50% population were suffering from periodontitis. However, the prevalence increases with age remarkably and it is investigated that a high prevalence (>50%) is affecting the elderly who is over 65 years old. There is an increasing interest in the direct and indirect relationships between periodontitis and hyperuricemia. Currently, hyperuricemia has become the second major metabolic disease in modern society and the prevalence of hyperuricemia among adult males and females was 21.7% and 14.4% respectively. As an inflammatory disease associated with various systemic diseases, periodontitis may have certain connections with hyperuricemia. Partial existing research announced that hyperuricemia could act as an inhibitory factor for periodontitis, while other scholars presented that a high uric acid (UA) level was more likely to aggravate inflammatory immune response and lead to more serious tissue destruction. This article provides a detailed and comprehensive overview of the relationship underlying hyperuricemia and periodontitis in the molecular mechanisms. Given the impact of hyperuricemia, this review could provide insight into its comorbidities.

Periodontal disease metabolomics signatures from different biofluids: a systematic review

BACKGROUND

Periodontitis is resulted from a complex interaction between genetics and epigenetics, microbial factors, and the host response. Metabolomics analyses reflect both the steady-state physiological equilibrium of cells or organisms as well as their dynamic metabolic responses to environmental stimuli.

AIM OF REVIEW

This systematic review of the literature aimed to assess which low molecular weight metabolites are more often found in biological fluids of individuals with periodontitis compared to individuals with gingivitis or periodontal health.

KEY SCIENTIFIC CONCEPTS OF REVIEW

All the included studies employed untargeted analysis. One or more biological fluids were analyzed, including saliva (n = 14), gingival crevicular fluid (n = 6), mouthwash (n = 1), serum (n = 3) and plasma (n = 1). Fifty-six main metabolites related to periodontitis have been identified in at least two independent studies by NMR spectroscopy or MS-based metabolomics. Saliva was the main biological fluid sampled. It is noteworthy that 14 metabolites of the 56 detected were identified as main metabolites in all studies that sampled the saliva. The majority of metabolites found consistently among studies were amino acids, organic acids and derivates: acetate, alanine, butyrate, formate, GABA, lactate, propionate, phenylalanine and valine. They were either up- or down-regulated in the studies or this information was not mentioned. The main metabolic pathway was related to phenylalanine, tyrosine and tryptophan biosynthesis. Metabolites more frequently found in individuals with periodontitis were related to both the host and to microorganism responses. Future studies are needed, and they should follow some methodological standards to facilitate their comparison.

Integrated analysis of the salivary microbiome and metabolome in chronic and aggressive periodontitis: A pilot study

This pilot study was designed to identify the salivary microbial community and metabolic characteristics in patients with generalized periodontitis. A total of 36 saliva samples were collected from 13 patients with aggressive periodontitis (AgP), 13 patients with chronic periodontitis (ChP), and 10 subjects with periodontal health (PH). The microbiome was evaluated using 16S rRNA gene high-throughput sequencing, and the metabolome was accessed using gas chromatography-mass spectrometry. The correlation between microbiomes and metabolomics was analyzed by Spearman’s correlation method. Our results revealed that the salivary microbial community and metabolite composition differed significantly between patients with periodontitis and healthy controls. Striking differences were found in the composition of salivary metabolites between AgP and ChP. The genera Treponema, Peptococcus, Catonella, Desulfobulbus, Peptostreptococcaceae_[XI] ([G-2], [G-3] [G-4], [G-6], and [G-9]), Bacteroidetes_[G-5], TM7_[G-5], Dialister, Eikenella, Fretibacterium, and Filifactor were present in higher levels in patients with periodontitis than in the healthy participants. The biochemical pathways that were significantly different between ChP and AgP included pyrimidine metabolism; alanine, aspartate, and glutamate metabolism; beta-alanine metabolism; citrate cycle; and arginine and proline metabolism. The differential metabolites between ChP and AgP groups, such as urea, beta-alanine, 3-aminoisobutyric acid, and thymine, showed the most significant correlations with the genera. These differential microorganisms and metabolites may be used as potential biomarkers to monitor the occurrence and development of periodontitis through the utilization of non-invasive and convenient saliva samples. This study reveals the integration of salivary microbial data and metabolomic data, which provides a foundation to further explore the potential mechanism of periodontitis.

Fusobacterium nucleatum Metabolically Integrates Commensals and Pathogens in Oral Biofilms

Fusobacterium nucleatum is a common constituent of the oral microbiota in both periodontal health and disease. Previously, we discovered ornithine cross-feeding between F. nucleatum and Streptococcus gordonii, where S. gordonii secretes ornithine via an arginine-ornithine antiporter (ArcD), which in turn supports the growth and biofilm development of F. nucleatum; however, broader metabolic aspects of F. nucleatum within polymicrobial communities and their impact on periodontal pathogenesis have not been addressed. Here, we show that when cocultured with S. gordonii, F. nucleatum increased amino acid availability to enhance the production of butyrate and putrescine, a polyamine produced by ornithine decarboxylation. Coculture with Veillonella parvula, another common inhabitant of the oral microbiota, also increased lysine availability, promoting cadaverine production by F. nucleatum. We confirmed that ArcD-dependent S. gordonii-excreted ornithine induces synergistic putrescine production, and mass spectrometry imaging revealed that this metabolic capability creates a putrescine-rich microenvironment on the surface of F. nucleatum biofilms. We further demonstrated that polyamines caused significant changes in the biofilm phenotype of a periodontal pathogen, Porphyromonas gingivalis, with putrescine accelerating the biofilm life cycle of maturation and dispersal. This phenomenon was also observed with putrescine derived from S. gordonii-F. nucleatum coculture. Lastly, analysis of plaque samples revealed cooccurrence of P. gingivalis with genetic modules for putrescine production by S. gordonii and F. nucleatum. Overall, our results highlight the ability of F. nucleatum to induce synergistic polyamine production within multispecies consortia and provide insight into how the trophic web in oral biofilm ecosystems can eventually shape disease-associated communities.

IMPORTANCE Periodontitis is caused by a pathogenic shift in subgingival biofilm ecosystems, which is accompanied by alterations in microbiome composition and function, including changes in the metabolic activity of the biofilm, which comprises multiple commensals and pathogens. While Fusobacterium nucleatum is a common constituent of the supra- and subgingival biofilms, its metabolic integration within polymicrobial communities and the impact on periodontal pathogenesis are poorly understood. Here, we report that amino acids supplied by other commensal bacteria induce polyamine production by F. nucleatum, creating polyamine-rich microenvironments. Polyamines reportedly have diverse functions in bacterial physiology and possible involvement in periodontal pathogenesis. We show that the F. nucleatum-integrated trophic network yielding putrescine from arginine through ornithine accelerates the biofilm life cycle of Porphyromonas gingivalis, a periodontal pathogen, from the planktonic state through biofilm formation to dispersal. This work provides insight into how cooperative metabolism within oral biofilms can tip the balance toward periodontitis.

The role of oral microbiome in periodontitis under diabetes mellitus

Periodontitis is among most common human inflammatory diseases and characterized by destruction of tooth-supporting tissues that will eventually lead to tooth loss. Diabetes mellitus (DM) is a group of metabolic disorders characterized by chronic hyperglycemia which results from defects in insulin secretion and/or insulin resistance. Numerous studies have provided evidence for the inter-relationship between DM and periodontitis that has been considered as the sixth most frequent complication of DM. However, the mechanisms are not fully understood yet. The impact of DM on periodontitis through hyperglycemia and inflammatory pathways is well described, but the effects of DM on oral microbiota remain controversial according to previous studies. Recent studies using next-generation sequencing technology indicate that DM can alter the biodiversity and composition of oral microbiome especially subgingival microbiome. This may be another mechanism by which DM risks or aggravates periodontitis. Thus, to understand the role of oral microbiome in periodontitis of diabetics and the mechanism of shifts of oral microbiome under DM would be valuable for making specific therapeutic regimens for treating periodontitis patients with DM or preventing diabetic patients from periodontitis. This article reviews the role of oral microbiome in periodontal health (symbiosis) and disease (dysbiosis), highlights the oral microbial shifts under DM and summarizes the mechanism of the shifts.

Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence

Plaque is a bacterial biofilm that adheres to each other and exists on the tooth surface, and new plaque can continuously reform after removing it from the tooth surface. The pathogenesis of periodontal disease is related to the bacteria, the host and the environment, with the bacteria and bacterial products in plaque being the main initiators of periodontal disease. The effective control of plaque is an effective method for the treatment and prevention of periodontal disease and is often underappreciated in clinical practice. For the traditional diagnostic method through experience and visual observation, it may lead to misdiagnosis and underdiagnosis. In order to accurately diagnose plaque disease, this study designed a convolutional neural network-based oral dental disease diagnosis system for oral care interventions to improve oral health awareness. Thus motivate patients to implement proper oral health care measures, and continuously and lifelong insist on thorough daily plaque removal to improve patients' physical health and quality of life in periodontal disease patients.

Metabolomics: Paving the path for personalized periodontics - A literature review

The pathogenesis of periodontal disease is governed by a multitude of factors ranging from the macroscopic to the microscopic scale. Among the factors that constitute the etiological agents of the disease, a major element is the role played by the body's metabolome-i.e., the complete collection of microscopic molecules and metabolic products of cells and tissues in the body. Being of a regulatory nature, the interplay of these molecules exerts a considerable effect on the development as well as the progression of disease, which differs in each individual based on their phenotype. Exploring this connection and application into the field of diagnostic as well as prediction of risk for periodontitis will ultimately result in a personalized standard of care for patients in the future.

Subgingival microbiome in periodontitis and type 2 diabetes mellitus: an exploratory study using metagenomic sequencing

Purpose

To explore differences in the subgingival microbiome according to the presence of periodontitis and/or type 2 diabetes mellitus (T2D), a metagenomic sequencing analysis of the subgingival microbiome was performed.

Methods

Twelve participants were divided into 4 groups based on their health conditions (periodontitis, T2D, T2D complicated with periodontitis, and generally healthy). Subgingival plaque was collected for metagenomic sequencing, and gingival crevicular fluids were collected to analyze the concentrations of short-chain fatty acids.

Results

The shifts in the subgingival flora from the healthy to periodontitis states were less prominent in T2D subjects than in subjects without T2D. The pentose and glucuronate interconversion, fructose and mannose metabolism, and galactose metabolism pathways were enriched in the periodontitis state, while the phosphotransferase system, lipopolysaccharide (LPS) and peptidoglycan biosynthesis, bacterial secretion system, sulfur metabolism, and glycolysis pathways were enriched in the T2D state. Multiple genes whose expression was upregulated from the red and orange complex bacterial genomes were associated with bacterial biofilm formation and pathogenicity. The concentrations of propionic acid and butyric acid were significantly higher in subjects with periodontitis, with or without T2D, than in healthy subjects.

Conclusions

T2D patients are more susceptible to the presence of periodontal pathogens and have a higher risk of developing periodontitis. The pentose and glucuronate interconversion, fructose and mannose metabolism, galactose metabolism, and glycolysis pathways may represent the potential microbial functional association between periodontitis and T2D, and butyric acid may play an important role in the interaction between these 2 diseases. The enrichment of the LPS and peptidoglycan biosynthesis, bacterial secretion system, and sulfur metabolism pathways may cause T2D patients to be more susceptible to periodontitis.

A review on natural teeth whitening

BACKGROUND

Discoloration of teeth occurs for various reasons. Common ingredients like substances from tea and coffee, as well as antibiotics like tetracycline, or food dyes, can percolate into the teeth, and, as such, these stains may persist in the porous structure of the enamel. Smoking is also contributory to dental discoloration, with toxins of tobacco smoke accumulating in a similar way. With aging, teeth tend to be discolored with accumulation of various stains in addition to the enamel gradually eroding to expose the yellow dentin.

HIGHLIGHT

This review focused on the effect of several natural ingredients with teeth-whitening properties and their daily clinical application. Metabolic dental bleaching mechanisms, as well as tooth discoloration and decay, were also reviewed. The current scientific literature (mostly from 2000 to 2020) was consolidated from manuscripts retrieved from Scopus, PubMed, ResearchGate, and Google Scholar.

CONCLUSION

Natural teeth whitening effectively lightens the natural color of teeth without eroding dental surfaces. On the other hand, commercially available whiteners containing hydrogen peroxide and carbamide peroxide, in high concentrations, can lead to deproteinization and demineralization of teeth through oxidation processes. If used extensively, these compounds may cause a number of adverse effects. Alternative natural teeth-whiteners include ingredients like lemons, strawberries, oranges, papaya, and other fruits. Such natural ingredients offer a milder and safer way of whitening teeth than whiteners containing hydrogen peroxide or carbamide peroxide.

Potential of Prebiotic D-Tagatose for Prevention of Oral Disease

Recent studies have shown phenotypic and metabolic heterogeneity in related species including Streptococcus oralis, a typical oral commensal bacterium, Streptococcus mutans, a cariogenic bacterium, and Streptococcus gordonii, which functions as an accessory pathogen in periodontopathic biofilm. In this study, metabolites characteristically contained in the saliva of individuals with good oral hygiene were determined, after which the effects of an identified prebiotic candidate, D-tagatose, on phenotype, gene expression, and metabolic profiles of those three key bacterial species were investigated. Examinations of the saliva metabolome of 18 systemically healthy volunteers identified salivary D-tagatose as associated with lower dental biofilm abundance in the oral cavity (Spearman’s correlation coefficient; r = -0.603, p = 0.008), then the effects of D-tagatose on oral streptococci were analyzed in vitro. In chemically defined medium (CDM) containing D-tagatose as the sole carbohydrate source, S. mutans and S. gordonii each showed negligible biofilm formation, whereas significant biofilms were formed in cultures of S. oralis. Furthermore, even in the presence of glucose, S. mutans and S. gordonii showed growth suppression and decreases in the final viable cell count in a D-tagatose concentration-dependent manner. In contrast, no inhibitory effects of D-tagatose on the growth of S. oralis were observed. To investigate species-specific inhibition by D-tagatose, the metabolomic profiles of D-tagatose-treated S. mutans, S. gordonii, and S. oralis cells were examined. The intracellular amounts of pyruvate-derived amino acids in S. mutans and S. gordonii, but not in S. oralis, such as branched-chain amino acids and alanine, tended to decrease in the presence of D-tagatose. This phenomenon indicates that D-tagatose inhibits growth of those bacteria by affecting glycolysis and its downstream metabolism. In conclusion, the present study provides evidence that D-tagatose is abundant in saliva of individuals with good oral health. Additionally, experimental results demonstrated that D-tagatose selectively inhibits growth of the oral pathogens S. mutans and S. gordonii. In contrast, the oral commensal S. oralis seemed to be negligibly affected, thus highlighting the potential of administration of D-tagatose as an oral prebiotic for its ability to manipulate the metabolism of those targeted oral streptococci.

Saliva and Plasma Reflect Metabolism Altered by Diabetes and Periodontitis

Periodontitis is an inflammatory disorder caused by disintegration of the balance between the periodontal microbiome and host response. While growing evidence suggests links between periodontitis and various metabolic disorders including type 2 diabetes (T2D), non-alcoholic liver disease, and cardiovascular disease (CVD), which often coexist in individuals with abdominal obesity, factors linking periodontal inflammation to common metabolic alterations remain to be fully elucidated. More detailed characterization of metabolomic profiles associated with multiple oral and cardiometabolic traits may provide better understanding of the complexity of oral-systemic crosstalk and its underlying mechanism. We performed comprehensive profiling of plasma and salivary metabolomes using untargeted gas chromatography/mass spectrometry to investigate multivariate covariation with clinical markers of oral and systemic health in 31 T2D patients with metabolic comorbidities and 30 control subjects. Orthogonal partial least squares (OPLS) results enabled more accurate characterization of associations among 11 oral and 25 systemic clinical outcomes, and 143 salivary and 78 plasma metabolites. In particular, metabolites that reflect cardiometabolic changes were identified in both plasma and saliva, with plasma and salivary ratios of (mannose + allose):1,5-anhydroglucitol achieving areas under the curve of 0.99 and 0.92, respectively, for T2D diagnosis. Additionally, OPLS analysis of periodontal inflamed surface area (PISA) as the numerical response variable revealed shared and unique responses of metabolomic and clinical markers to PISA between healthy and T2D groups. When combined with linear regression models, we found a significant correlation between PISA and multiple metabolites in both groups, including threonate, cadaverine and hydrocinnamate in saliva, as well as lactate and pentadecanoic acid in plasma, of which plasma lactate showed a predominant trend in the healthy group. Unique metabolites associated with PISA in the T2D group included plasma phosphate and salivary malate, while those in the healthy group included plasma gluconate and salivary adenosine. Remarkably, higher PISA was correlated with altered hepatic lipid metabolism in both groups, including higher levels of triglycerides, aspartate aminotransferase and alanine aminotransferase, leading to increased risk of cardiometabolic disease based on a score summarizing levels of CVD-related biomarkers. These findings revealed the potential utility of saliva for evaluating the risk of metabolic disorders without need for a blood test, and provide evidence that disrupted liver lipid metabolism may underlie the link between periodontitis and cardiometabolic disease.

Association Between the Extent of Periodontal Inflammation and the Severity of Rheumatoid Arthritis in Japanese Patients With Rheumatoid Arthritis

OBJECTIVE

Periodontal inflammation can affect the progression of rheumatoid arthritis (RA), and RA drugs may influence the periodontal condition of patients with RA. We examined whether the association between periodontal inflammation and the severity of RA is influenced by RA medication.

METHODS

This cross-sectional study recruited 98 Japanese patients with RA from an orthopaedic clinic. We assessed the severity of RA using the Steinbrocker class and stage. The periodontal inflamed surface area (PISA) was used as an indicator of periodontal status. We obtained data on RA medications from medical records. We examined the associations among periodontal tissue inflammation, RA medications, and RA severity using multinomial logistic regression analyses.

RESULTS

In univariate multinomial logistic regression analyses, no significant association between PISA score and RA severity was observed. There was no significant association between PISA score and RA severity in multivariate analyses not including variables about RA drugs as independent variables. However, in multivariate analyses adjusted for RA drugs and other confounding variables, patients with a PISA >550 mm2 had significantly higher odds ratios (ORs) for Steinbrocker class III-IV and stage III-IV (OR, 20.24; 95% confidence interval [CI], 1.78-229.85 and OR, 12.42; 95% CI, 1.79-86.49, respectively) compared to patients with PISA score ≤550 mm2.

CONCLUSION

The extent of periodontal inflammation is associated with the severity of RA independent of RA medications.

Proteomics, lipidomics, metabolomics and 16S DNA sequencing of dental plaque from patients with diabetes and periodontal disease

Oral microbiome influences human health, specifically prediabetes and type 2 diabetes (Pre-DM/DM) and periodontal diseases (PDs), through complex microbial interactions. To explore these relations, we performed 16S rDNA sequencing, metabolomics, lipidomics, and proteomics analyses on supragingival dental plaque collected from individuals with Pre-DM/DM (n = 39), Pre-DM/DM and PD (n = 37), PD alone (n = 11), or neither (n = 10). We identified on average 2790 operational taxonomic units and 2025 microbial and host proteins per sample and quantified 110 metabolites and 415 lipids. Plaque samples from Pre-DM/DM patients contained higher abundance of Fusobacterium and Tannerella than plaques from metabolically healthy patients. Phosphatidylcholines, plasmenyl phosphatidylcholines, ceramides containing non-OH fatty acids, and host proteins related to actin filament rearrangement were elevated in plaques from PD versus non-PD samples. Cross-omic correlation analysis enabled the detection of a strong association between Lautropia and monomethyl phosphatidylethanolamine (PE-NMe), which is striking because synthesis of PE-NMe is uncommon in oral bacteria. Lipidomics analysis of in vitro cultures of Lautropia mirabilis confirmed the synthesis of PE-NMe by the bacteria. This comprehensive analysis revealed a novel microbial metabolic pathway and significant associations of host-derived proteins with PD.

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Patients with periodontal disease or diabetes have unique microbial dysbiosis.

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Proteomics and 16S data provide complementary information about microbial diversity.

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Cross-omic correlation reveals host signatures associated with periodontal disease.

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Multi-omic data lead to finding about microbially synthesized lipids.

Periodontal inflamed surface area is associated with hs-CRP in septuagenarian Japanese adults in cross-sectional findings from the SONIC study

Periodontal disease is a chronic inflammatory condition that affects various peripheral organs. The periodontal inflamed surface area (PISA) quantifies periodontitis severity and the spread of inflammatory wounds. This study aimed to investigate the association between PISA and high-sensitivity C-reactive protein (hs-CRP), a systemic inflammation marker. This study included 250 community-dwelling septuagenarians (69-71 years). We collected information on their medical (e.g., diabetes and dyslipidemia) and dental examinations (e.g., measurement of the probing pocket depth). Generalized linear model analysis was used to explore the association between PISA and hs-CRP levels. There was a significant difference in hs-CRP levels between groups with PISA ≥ 500 and < 500 (p = 0.017). Moreover, the generalized linear model analysis revealed a significant association between PISA and hs-CRP levels (risk ratio = 1.77; p = 0.033) even after adjusting other factors. Further, we found a correlation between PISA and hs-CRP (Spearman's rank correlation coefficient, rs = 0.181; p = 0.023). Our findings suggest that PISA is an effective index for estimating the effect of periodontitis on the whole body, enabling medical-dental cooperation.

Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting

BACKGROUND

Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss.

METHODS

We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models.

RESULTS

We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation.

CONCLUSIONS

Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss.

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.

Taxonomic and Gene Category Analyses of Subgingival Plaques from a Group of Japanese Individuals with and without Periodontitis

Periodontitis is an inflammation of tooth-supporting tissues, which is caused by bacteria in the subgingival plaque (biofilm) and the host immune response. Traditionally, subgingival pathogens have been investigated using methods such as culturing, DNA probes, or PCR. The development of next-generation sequencing made it possible to investigate the whole microbiome in the subgingival plaque. Previous studies have implicated dysbiosis of the subgingival microbiome in the etiology of periodontitis. However, details are still lacking. In this study, we conducted a metagenomic analysis of subgingival plaque samples from a group of Japanese individuals with and without periodontitis. In the taxonomic composition analysis, genus Bacteroides and Mycobacterium demonstrated significantly different compositions between healthy sites and sites with periodontal pockets. The results from the relative abundance of functional gene categories, carbohydrate metabolism, glycan biosynthesis and metabolism, amino acid metabolism, replication and repair showed significant differences between healthy sites and sites with periodontal pockets. These results provide important insights into the shift in the taxonomic and functional gene category abundance caused by dysbiosis, which occurs during the progression of periodontal disease.

Whole-body insulin resistance and energy expenditure indices, serum lipids, and skeletal muscle metabolome in a state of lipoprotein lipase overexpression

INTRODUCTION

Overexpression of lipoprotein lipase (LPL) protects against high-fat-diet (HFD)-induced obesity and insulin resistance in transgenic rabbits; however, the molecular mechanisms remain unclear. Skeletal muscle is a major organ responsible for insulin-stimulated glucose uptake and energy expenditure.

OBJECTIVES

The main purpose of the current study was to examine the effects of the overexpression of LPL on the skeletal muscle metabolomic profiles to test our hypothesis that the mitochondrial oxidative metabolism would be activated in the skeletal muscle of LPL transgenic rabbits and that the higher mitochondrial oxidative metabolism activity would confer better phenotypic metabolic outcomes.

METHODS

Under a HFD, insulin resistance index was measured using the intravenous glucose tolerance test, and total energy expenditure (TEE) was measured by doubly-labeled water in control and LPL transgenic rabbits (n = 12, each group). Serum lipids, such as triglycerides and free fatty acid, were also measured. The skeletal muscle metabolite profile was analyzed using capillary electrophoresis time-of flight mass spectrometry in the two groups (n = 9, each group). A metabolite set enrichment analysis (MSEA) with muscle metabolites and a false discovery rate q < 0.2 was performed to identify significantly different metabolic pathways between the 2 groups.

RESULTS

The triglycerides and free fatty acid levels and insulin resistance index were lower, whereas the TEE was higher in the LPL transgenic rabbits than in the control rabbits. Among 165 metabolites detected, the levels of 37 muscle metabolites were significantly different between the 2 groups after false discovery rate correction (q < 0.2). The MSEA revealed that the TCA cycle and proteinogenic amino acid metabolism pathways were significantly different between the 2 groups (P < 0.05). In the MSEA, all four selected metabolites for the TCA cycle (2-oxoglutaric acid, citric acid, malic acid, fumaric acid), as well as eight selected metabolites for proteinogenic amino acid metabolism (asparagine, proline, methionine, phenylalanine, histidine, arginine, leucine, isoleucine) were consistently increased in the transgenic rabbits compared with control rabbits, suggesting that these two metabolic pathways were activated in the transgenic rabbits. Some of the selected metabolites, such as citric acid and methionine, were significantly associated with serum lipids and insulin resistance (P < 0.05).

CONCLUSION

The current results suggest that the overexpression of LPL may lead to increased activities of TCA cycle and proteinogenic amino acid metabolism pathways in the skeletal muscle, and these enhancements may play an important role in the biological mechanisms underlying the anti-obesity/anti-diabetes features of LPL overexpression.

Estimation of the Periodontal Inflamed Surface Area by Simple Oral Examination

The periodontal inflamed surface area (PISA) is a useful index for clinical and epidemiological assessments, since it can represent the inflammation status of patients in one contentious variable. However, calculation of the PISA is difficult, requiring six point probing depth measurements with or without bleeding on probing on 28 teeth, followed by data input in a calculation program. More simple methods are essential for screening periodontal disease or in epidemiological studies. In this study, we tried to establish a convenient partial examination method to estimate PISA. Cross-sectional data of 254 subjects who completed active periodontal therapy were analyzed. Teeth that represent the PISA value were selected by an item response theory approach. The maxillary second molar, first premolar, and lateral incisor and the mandibular second molar and lateral incisor were selected. The sum of the PISAs of these teeth was significantly correlated with the patient’s PISA (R² = 0.938). More simply, the sum of the maximum values of probing pocket depth with bleeding for these teeth were also significantly correlated with the patient’s PISA (R² = 0.6457). The simple model presented in this study may be useful to estimate PISA.

Polyamine biomarkers as indicators of human disease

The significant increase of periodontitis, chronic kidney disease (CKD), Alzheimer's disease and cancer can be attributed to an ageing population. Each disease produces a range of biomarkers that can be indicative of disease onset and progression. Biomarkers are defined as cellular (intra/extracellular components and whole cells), biochemical (metabolites, ions and toxins) or molecular (nucleic acids, proteins and lipids) alterations which are measurable in biological media such as human tissues, cells or fluids. An interesting group of biomarkers that merit further investigation are the polyamines. Polyamines are a group of molecules consisting of cadaverine, putrescine, spermine and spermidine and have been implicated in the development of a range of systemic diseases, in part due to their production in periodontitis. Cadaverine and putrescine within the periodontal environment have demonstrated cell signalling interfering abilities, by way of leukocyte migration disruption. The polyamines spermine and spermidine in tumour cells have been shown to inhibit cellular apoptosis, effectively prolonging tumorigenesis and continuation of cancer within the host. Polyamine degradation products such as acrolein have been shown to exacerbate renal damage in CKD patients. Thus, the use of such molecules has merit to be utilized in the early indication of such diseases in patients.

Salivary metabolomics for the diagnosis of periodontal diseases: a systematic review with methodological quality assessment

INTRODUCTION

Early diagnosis of periodontitis by means of a rapid, accurate and non-invasive method is highly desirable to reduce the individual and epidemiological burden of this largely prevalent disease.

OBJECTIVES

The aims of the present systematic review were to examine potential salivary metabolic biomarkers and pathways associated to periodontitis, and to assess the accuracy of salivary untargeted metabolomics for the diagnosis of periodontal diseases.

METHODS

Relevant studies identified from MEDLINE (PubMed), Embase and Scopus databases were systematically examined for analytical protocols, metabolic biomarkers and results from the multivariate analysis (MVA). Pathway analysis was performed using the MetaboAnalyst online software and quality assessment by means of a modified version of the QUADOMICS tool.

RESULTS

Twelve studies met the inclusion criteria, with sample sizes ranging from 19 to 130 subjects. Compared to periodontally healthy individuals, valine, phenylalanine, isoleucine, tyrosine and butyrate were found upregulated in periodontitis patients in most studies; while lactate, pyruvate and N-acetyl groups were the most significantly expressed in healthy individuals. Metabolic pathways that resulted dysregulated are mainly implicated in inflammation, oxidative stress, immune activation and bacterial energetic metabolism. The findings from MVA revealed that periodontitis is characterized by a specific metabolic signature in saliva, with coefficients of determination ranging from 0.52 to 0.99.

CONCLUSIONS

This systematic review summarizes candidate metabolic biomarkers and pathways related to periodontitis, which may provide opportunities for the validation of diagnostic or predictive models and the discovery of novel targets for monitoring and treating such a disease (PROSPERO CRD42020188482).

Evaluation of Single Sample Network Inference Methods for Metabolomics-Based Systems Medicine

Networks and network analyses are fundamental tools of systems biology. Networks are built by inferring pair-wise relationships among biological entities from a large number of samples such that subject-specific information is lost. The possibility of constructing these sample (individual)-specific networks from single molecular profiles might offer new insights in systems and personalized medicine and as a consequence is attracting more and more research interest. In this study, we evaluated and compared LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples) and ssPCC (single sample network based on Pearson correlation) in the metabolomics context of metabolite–metabolite association networks. We illustrated and explored the characteristics of these two methods on (i) simulated data, (ii) data generated from a dynamic metabolic model to simulate real-life observed metabolite concentration profiles, and (iii) 22 metabolomic data sets and (iv) we applied single sample network inference to a study case pertaining to the investigation of necrotizing soft tissue infections to show how these methods can be applied in metabolomics. We also proposed some adaptations of the methods that can be used for data exploration. Overall, despite some limitations, we found single sample networks to be a promising tool for the analysis of metabolomics data.

Gingival fibroblasts dynamically reprogram cellular metabolism during infection of Porphyromonas gingivalis

OBJECTIVE

The purpose of the present study was to explore the sequential changes in the cellular metabolism in gingival fibroblasts (GFs) in response toPorphyromonas gingvalis (P. gingivalis) ATCC33277 infection.

DESIGN

GFs were treated withP. gingivalis at the MOI of 50 for 4, 24 and 48 h to mimic the early, medium, and late phase in the bacterial infection. LDH assay and cell counting kit-8 were utilized to explore cell death and proliferation. Real-time PCR was utilized to explore the gene transcription of pro-inflammatory genes. The relative levels of biomolecules in GFs were measured by gas chromatography-mass spectrometry. Principal component analysis and orthogonal partial least-squares-discriminant analysis were performed to visualize the metabolic difference among experimental groups. In addition, pathway analysis was conducted regarding differential metabolites in GFs.

RESULTS

P. gingivalis infection triggered significant gene transcription of IL-1β, IL 6, MCP 1, and MMP 1 in GFs. In addition, P. gingivalis stimulated cell proliferation of GFs at MOI of 10, 50 and 250. Moreover, P. gingivalis triggered significant cell death at higher MOI. 69, 173 and 148 metabolites were qualitatively detected at 4, 24 and 48 h after P. gingivalis infection respectively in GFs, showing a sequential change of different phase. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated that ATP-binding cassette transporters, glutathione, purine and pyrimidine metabolism was significantly altered in different phase.

CONCLUSIONS

Human GFs may sequentially rewire metabolomics to shape the inflammatory responses and support the proliferation of host cells during P. gingivalis infection.

Polyamines in the virulence of bacterial pathogens of respiratory tract

Polyamines are positively charged hydrocarbons that are essential for the growth and cellular maintenance in prokaryotes and eukaryotes. Polyamines have been demonstrated to play a role in bacterial pathogenicity and biofilm formation. However, the role of extracellular polyamines as a signaling molecule in the regulation of virulence is not investigated in detail. The bacterial pathogens residing in the respiratory tract remain asymptomatic for an extended period; however, the factors that lead to symptomatic behavior are poorly understood. Further investigation to understand the relation between the host-secreted factors and virulence of pathogenic bacteria in the respiratory tract may provide insights into the pathogenesis of respiratory tract infections. Polyamines produced within the bacterial cell are generally sequestered. Therefore, the pool of extracellular polyamines formed by secretion of the commensals and the host may be one of the signaling molecules that might contribute toward the alterations in the expression of virulence factors in bacterial pathogens. Besides, convergent mechanisms of polyamine biosynthesis do exist across the border of species and genus level. Also, several novel polyamine transporters in the host and bacteria remain yet to be identified. The review focuses on the role of polyamines in the expression of virulence phenotypes and biofilm formation of the respiratory tract pathogens.

The Role of Oral Microbiota in Intra-Oral Halitosis

Halitosis is a common ailment concerning 15% to 60% of the human population. Halitosis can be divided into extra-oral halitosis (EOH) and intra-oral halitosis (IOH). The IOH is formed by volatile compounds, which are produced mainly by anaerobic bacteria. To these odorous substances belong volatile sulfur compounds (VSCs), aromatic compounds, amines, short-chain fatty or organic acids, alcohols, aliphatic compounds, aldehydes, and ketones. The most important VSCs are hydrogen sulfide, dimethyl sulfide, dimethyl disulfide, and methyl mercaptan. VSCs can be toxic for human cells even at low concentrations. The oral bacteria most related to halitosis are Actinomyces spp., Bacteroides spp., Dialister spp., Eubacterium spp., Fusobacterium spp., Leptotrichia spp., Peptostreptococcus spp., Porphyromonas spp., Prevotella spp., Selenomonas spp., Solobacterium spp., Tannerella forsythia, and Veillonella spp. Most bacteria that cause halitosis are responsible for periodontitis, but they can also affect the development of oral and digestive tract cancers. Malodorous agents responsible for carcinogenesis are hydrogen sulfide and acetaldehyde.

Pharmacodynamic and Metabolomics Studies on the Effect of Kouyanqing Granule in the Treatment of Phenol-Induced Oral Ulcer Worsened by Sleep Deprivation

Oral ulcers are the most prevalent oral mucosal diseases globally, and no specific treatment schemes are currently available due to the complexity of oral ulcer diseases. Sleep deprivation increases the risk of a deterioration in oral health. Kouyanqing Granule (KYQG) has been used for decades in China to treat inflammatory diseases of the mouth and throat associated with the hyperactivity of fire due to yin deficiency syndrome. However, the mechanisms underlying the effects of KYQG in the treatment of oral ulcers are still unclear. The aims of this study were to investigate whether KYQG treatment could attenuate the symptoms of oral ulcers worsened by sleep deprivation and identify the involved metabolic pathways. First, we conducted chemical profiling of KYQG via UPLC–MS analysis. We then combined pharmacological and metabolomics approaches in a phenol-induced rat model of oral ulcers worsened by sleep deprivation. A total of 79 compounds were initially identified. Our observations showed that KYQG treatment induced a significantly higher healing rate in oral ulcers worsened by sleep deprivation. KYQG significantly reduced the levels of 5-HT and GABA in serum, and only decreased the 5-HT level in brain tissue after phenol injury followed by sleep deprivation. Moreover, KYQG administration significantly suppressed systemic inflammation by inhibiting TNF-α, IL-1β, IL-6, IL-18, and MCP-1. Immunohistochemical analysis further revealed that KYQG inhibited IL-6 expression in buccal mucosa tissues. KYQG treatment also significantly decreased the serum levels of ACTH, CORT, IgM, and 8-OHdG. Serum metabolomics analysis showed that a total of 30 metabolites showed significant differential abundances under KYQG intervention, while metabolic pathway analysis suggested that the altered metabolites were associated with the dysregulation of eight metabolic pathways. Taken together, our results indicated that KYQG attenuates the symptoms of oral ulcers worsened by sleep deprivation probably through the regulation of the neuroimmunoendocrine system, oxidative stress levels, and tryptophan metabolism. This study also provides a novel approach for addressing the increased health risks resulting from sleep deficiency using an herbal medicine formula.

On the Use of Correlation and MI as a Measure of Metabolite-Metabolite Association for Network Differential Connectivity Analysis

Metabolite differential connectivity analysis has been successful in investigating potential molecular mechanisms underlying different conditions in biological systems. Correlation and Mutual Information (MI) are two of the most common measures to quantify association and for building metabolite-metabolite association networks and to calculate differential connectivity. In this study, we investigated the performance of correlation and MI to identify significantly differentially connected metabolites. These association measures were compared on (i) 23 publicly available metabolomic data sets and 7 data sets from other fields, (ii) simulated data with known correlation structures, and (iii) data generated using a dynamic metabolic model to simulate real-life observed metabolite concentration profiles. In all cases, we found more differentially connected metabolites when using correlation indices as a measure for association than MI. We also observed that different MI estimation algorithms resulted in difference in performance when applied to data generated using a dynamic model. We concluded that there is no significant benefit in using MI as a replacement for standard Pearson's or Spearman's correlation when the application is to quantify and detect differentially connected metabolites.

Microbiota and Malodor-Etiology and Management

Accumulating evidence indicates that microbiota plays a critical role in physiological processes in humans. However, it might also contribute to body malodor by producing numerous odorous molecules such as ammonia, volatile sulfur compounds or trimethylamine. Although malodor is commonly overlooked by physicians, it constitutes a major problem for many otherwise healthy people. Thus, this review aims to investigate most common causes of malodor and describe potential therapeutic options. We searched PUBMED and Google Scholar databases to identify the clinical and pre-clinical studies on bad body smell, malodor, halitosis and microbiota. Unpleasant smell might originate from the mouth, skin, urine or reproductive fluids and is usually caused by odorants that are produced by resident bacterial flora. The accumulation of odorous compounds might result from diet, specific composition of microbiota, as well as compromised function of the liver, intestines and kidneys. Evidence-based guidelines for management of body malodor are lacking and no universal treatment exists. However, the alleviation of the symptoms may be achieved by controlling the diet and physical elimination of bacteria and/or accumulated odorants.

Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

Periodontal studies using transcriptomics, proteomics, and metabolomics encompass the collection of mRNA transcripts, proteins, and small-molecule chemicals in the context of periodontal health and disease. The number of studies using these approaches has significantly increased in the last decade and they have provided new insight into the pathogenesis and host-microbe interactions that define periodontal diseases. This review provides an overview of current molecular findings using -omic approaches that underlie periodontal disease, including modulation of the host immune response, tissue homeostasis, and complex metabolic processes of the host and the oral microbiome. Integration of these -omic approaches will broaden our perspective of the molecular mechanisms involved in periodontal disease, advancing and improving the diagnosis and treatment of various stages and forms of periodontal disease.

The Nexus Between Periodontal Inflammation and Dysbiosis

The nexus between periodontal inflammation and the polymicrobial biofilm in the gingival sulcus is critical to understanding the pathobiology of periodontitis. Both play a major role in the etiology and pathogenesis of periodontal diseases and each reinforces the other. However, this nexus is also at the center of a significant conundrum for periodontology. For all mucosal polymicrobial biofilms, the most confounding issue is the paradoxical relationship between inflammation, infection, and disease. Despite significant advances made in both periodontal microbiology and periodontal pathobiology, the issue of which comes first, the inflammatory response or the change to a dysbiotic subgingival microbiota, is still debated. In this paper, we present a model for the pathogenesis of periodontitis based on the central role of inflammation and how this modulates the polymicrobial biofilm within the context of the continuum of health, gingivitis, and periodontitis. We propose a new model termed “Inflammation-Mediated Polymicrobial-Emergence and Dysbiotic-Exacerbation” (IMPEDE), which is designed to integrate into and complement the 2017 World Workshop Classification of Periodontitis.

Hyperuricemia as a potential plausible risk factor for periodontitis

Elevated blood uric acid (UA) levels have been positively associated with the severity of periodontitis. It thus brings out a hypothesis that hyperuricemia, a pathological elevation of blood UA, might be a risk factor for periodontitis. Namely, periodontitis individuals with Hu might acquire more severe periodontal destruction compared to those without Hu. To support the hypothesis, four aspects of evidences are proposed. First, hyperuricemia and periodontitis share many metabolic and inflammatory comorbidities such as metabolic syndrome, diabetes and cardiovascular diseases which are commonly related to elevated UA levels and gout. Second, observational and interventional studies have found altered UA levels in blood and saliva in periodontitis patients or after periodontal treatment, suggesting an epidemiological connection between hyperuricemia and periodontitis. Third, plausible immuno-metabolic mechanisms by which hyperuricemia might promote the progression of periodontitis are suggested, such as impaired immune response, oxidative stress, pathological bone remodeling and dysbiosis. The last, our empirical data exhibited elevated UA levels in gingival tissue in periodontitis mice compared to controls. If the hypothesis is true, given the high prevalence of the two conditions, hyperuricemia would be a significant risk factor increasing the global burden of periodontal diseases. Evidences on a directional correlation between hyperuricemia and periodontitis are sparse. Longitudinal and experimental studies would be necessary to determine the magnitude of periodontal risk, if any, exacerbated by hyperuricemia and the underlying mechanisms.

Metabolomics reveals impact of seven functional foods on metabolic pathways in a gut microbiota model

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Metabolomics was employed to assess 7 functional foods impact on gut microbiota.

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Insights regarding how functional foods alter gut metabolic pathways is presented.

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Increased GABA production was observed in polyphenol rich functional food.

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Purine alkaloids served as direct substrate in microbiota metabolism.

Functional food defined as dietary supplements that in addition to their nutritional values, can beneficially modulate body functions becomes more and more popular but the reaction of the intestinal microbiota to it is largely unknown. In order to analyse the impact of functional food on the microbiota itself it is necessary to focus on the physiology of the microbiota, which can be assessed in a whole by untargeted metabolomics. Obtaining a detailed description of the gut microbiota reaction to food ingredients can be a key to understand how these organisms regulate and bioprocess many of these food components. Extracts prepared from seven chief functional foods, namely green tea, black tea, Opuntia ficus-indica (prickly pear, cactus pear), black coffee, green coffee, pomegranate, and sumac were administered to a gut consortium culture encompassing 8 microbes which are resembling, to a large extent, the metabolic activities found in the human gut. Samples were harvested at 0.5 and 24 h post addition of functional food extract and from blank culture in parallel and analysed for its metabolites composition using gas chromatography coupled to mass spectrometry detection (GC-MS). A total of 131 metabolites were identified belonging to organic acids, alcohols, amino acids, fatty acids, inorganic compounds, nitrogenous compounds, nucleic acids, phenolics, steroids and sugars, with amino acids as the most abundant class in cultures. Considering the complexity of such datasets, multivariate data analyses were employed to classify samples and investigate how functional foods influence gut microbiota metabolisms. Results from this study provided a first insights regarding how functional foods alter gut metabolism through either induction or inhibition of certain metabolic pathways, i.e. GABA production in the presence of higher acidity induced by functional food metabolites such as polyphenols. Likewise, functional food metabolites i.e., purine alkaloids acted themselves as direct substrate in microbiota metabolism.

Salivary Metabolomics Fingerprint of Chronic Apical Abscess with Sinus Tract: A Pilot Study

Chronic apical abscess (CAA) is a lesion of apical periodontitis mostly characterized by areas of liquefactive necrosis with disintegrating polymorphonuclear neutrophils surrounded by macrophages. Its presence leads to local bacterial infection, systemic inflammatory response, pain, and swelling. The use of a novel approach for the study of CAA, such as metabolomics, seems to be important since it has proved to be a powerful tool for biomarkers discovery which could give novel molecular insight on CAA. So, the aim of this study was to verify the possibility to identify the metabolic fingerprint of CAA through the analysis of saliva samples. Nineteen patients were selected for this study: eleven patients affected by CAA with a sinus tract constituted the study group whereas eight patients without clinical and radiographic signs of CAA formed the healthy control group. Saliva samples were collected from each subject and immediately frozen at −80°C. Metabolomic profiles were obtained using a gas chromatography/mass spectrometry instrument. Subsequently, in order to compare the two groups, a multivariate statistical model was built that resulted to be statistically significant. The class of metabolites characterizing the CAA patients was closely related to the bacterial catabolism, tissue necrosis, and presence of a sinus tract. These preliminary results, for the first time, indicate that saliva samples analyzed by means of GC/MS metabolomics may be useful for identifying the presence of CAA, leading to new insights into this disease.

A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification

INTRODUCTION

Metabolomics is increasingly being used in the clinical setting for disease diagnosis, prognosis and risk prediction. Machine learning algorithms are particularly important in the construction of multivariate metabolite prediction. Historically, partial least squares (PLS) regression has been the gold standard for binary classification. Nonlinear machine learning methods such as random forests (RF), kernel support vector machines (SVM) and artificial neural networks (ANN) may be more suited to modelling possible nonlinear metabolite covariance, and thus provide better predictive models.

OBJECTIVES

We hypothesise that for binary classification using metabolomics data, non-linear machine learning methods will provide superior generalised predictive ability when compared to linear alternatives, in particular when compared with the current gold standard PLS discriminant analysis.

METHODS

We compared the general predictive performance of eight archetypal machine learning algorithms across ten publicly available clinical metabolomics data sets. The algorithms were implemented in the Python programming language. All code and results have been made publicly available as Jupyter notebooks.

RESULTS

There was only marginal improvement in predictive ability for SVM and ANN over PLS across all data sets. RF performance was comparatively poor. The use of out-of-bag bootstrap confidence intervals provided a measure of uncertainty of model prediction such that the quality of metabolomics data was observed to be a bigger influence on generalised performance than model choice.

CONCLUSION

The size of the data set, and choice of performance metric, had a greater influence on generalised predictive performance than the choice of machine learning algorithm.

The subgingival microbiome associated with periodontitis in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a systemic disease, predisposing patients to other inflammatory conditions including periodontitis. The subgingival microbiome, a key player in periodontitis pathogenesis, is not well characterized in T2DM population. To better understand whether the subgingival microbiome is different between T2DM and systemically healthy, nondiabetic (ND) subjects, we performed a longitudinal analysis of the subgingival microbiome in T2DM patients (n = 15) compared with ND subjects (n = 16). Using metagenomic shotgun sequencing, we investigated the microbiome in the healthy periodontal state, periodontitis state, and resolved state after treatment. We found that in the periodontitis state, the shift in the subgingival microbiome from the healthy state was less prominent in T2DM compared with ND subjects, yet the clinical signs of disease were similar for both. Furthermore, we revealed highly correlated presence of pathogenic species in relative abundance not only in the periodontitis state, but also in the healthy state in T2DM, suggesting an elevated risk of progression to periodontitis in this cohort. We further investigated the functional potentials of the subgingival microbiome and identified a set of microbial marker genes associated with the clinical states. These genes were significantly enriched in 21 pathways, some of which are associated with periodontitis and some potentially link T2DM and periodontitis. This study identified the longitudinal changes of the subgingival microbiome associated with periodontitis in T2DM and suggests that T2DM patients are more susceptible to shifts in the subgingival microbiome toward dysbiosis, potentially due to impaired host metabolic and immune regulation.

The Saliva Metabolome in Association to Oral Health Status

Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites ( n = 284) obtained by mass spectrometry among a subsample ( n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites ( n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.