Salivary Microbiome Composition Research Articles

Salivary microbiome and hypertension in the Qatari population

BackgroundThe prevalence of hypertension in Qatar is 33 percent of the adult population. It is postulated that the salivary microbiome can regulate blood pressure (BP). However, limited investigations exist to prove this hypothesis. Therefore, we examined the difference in the salivary microbiome composition between hypertensive and normotensive Qatari subjects.MethodsA total of 1190 Qatar Genome Project (QGP) participants (Mean age = 43 years) were included in this study. BP for all participants was classified into Normal (n = 357), Stage1 (n = 336), and Stage2: (n = 161) according to the American Heart Association guidelines. 16S-rRNA libraries were sequenced and analyzed using QIIME-pipeline, and PICRUST was used to predict functional metabolic routes. Machine Learning (ML) strategies were applied to identify salivary microbiome-based predictors of hypertension.ResultsDifferential abundant analysis (DAA) revealed that Bacteroides and Atopobium were the significant members of the hypertensive groups. Alpha and beta diversity indices indicated dysbiosis between the normotensive and hypertensive groups. ML-based prediction models revealed that these markers could predict hypertension with an AUC (Area under the curve) of 0.89. Functional predictive analysis disclosed that Cysteine and Methionine metabolism and the sulphur metabolic pathways involving the renin-angiotensin system were significantly higher in the normotensive group. Therefore, members of Bacteroides and Atopobium can serve as predictors of hypertension. Likewise, Prevotella, Neisseria, and Haemophilus can be the protectors that regulate BP via nitric acid synthesis and regulation of the renin-angiotensin system.ConclusionIt is one of the first studies to assess salivary microbiome and hypertension as disease models in a large cohort of the Qatari population. Further research is needed to confirm these findings and validate the mechanisms involved.

Oral microbial communities in children, caregivers, and associations with salivary biomeasures and environmental tobacco smoke exposure.

Human oral microbial communities are diverse, with implications for oral and systemic health. Oral microbial communities change over time; thus, it is important to understand how healthy versus dysbiotic oral microbiomes differ, especially within and between families. There is also a need to understand how the oral microbiome composition is changed within an individual including by factors such as environmental tobacco smoke (ETS) exposure, metabolic regulation, inflammation, and antioxidant potential. Using archived saliva samples collected from caregivers and children during a 90-month follow-up assessment in a longitudinal study of child development in the context of rural poverty, we used 16S rRNA gene sequencing to determine the salivary microbiome. A total of 724 saliva samples were available, 448 of which were from caregiver/child dyads, an additional 70 from children and 206 from adults. We compared children's and caregivers' oral microbiomes, performed "stomatotype" analyses, and examined microbial relations with concentrations of salivary markers associated with ETS exposure, metabolic regulation, inflammation, and antioxidant potential (i.e., salivary cotinine, adiponectin, C-reactive protein, and uric acid) assayed from the same biospecimens. Our results indicate that children and caregivers share much of their oral microbiome diversity, but there are distinct differences. Microbiomes from intrafamily individuals are more similar than microbiomes from nonfamily individuals, with child/caregiver dyad explaining 52% of overall microbial variation. Notably, children harbor fewer potential pathogens than caregivers, and participants' microbiomes clustered into two groups, with major differences being driven by Streptococcus spp. Differences in salivary microbiome composition associated with ETS exposure, and taxa associated with salivary analytes representing potential associations between antioxidant potential, metabolic regulation, and the oral microbiome. IMPORTANCE The human oral cavity is a multi-environment habitat that harbors a diversity of microorganisms. This oral microbiome is often transmitted between cohabitating individuals, which may associate oral and systemic health within family members. Furthermore, family social ecology plays a significant role in childhood development, which may be associated with lifelong health outcomes. In this study, we collected saliva from children and their caregivers and used 16S rRNA gene sequencing to characterize their oral microbiomes. We also analyzed salivary biomeasures of environmental tobacco smoke exposure, metabolic regulation, inflammation, and antioxidant potential. We show there are differences in individuals' oral microbiomes mainly due to Streptococcus spp. that family members share much of their microbes, and several bacterial taxa associate with the selected salivary biomeasures. Our results suggest there are large-scale oral microbiome patterns, and there are likely relationships between oral microbiomes and the social ecology of families.

Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome

Dental caries is the most common chronic disease in children that causes negative effects on their health, development, and well-being. Early preventive interventions are key to reduce early childhood caries prevalence. An efficient strategy is to provide risk-based targeted prevention; however, this requires an accurate caries risk predictor, which is still lacking for infants before caries onset. We aimed to develop a caries prediction model based on the salivary microbiome of caries-free 1-y-old children. Using a nested case-control design within a prospective cohort study, we selected 30 children based on their caries status at 1-y follow-up (at 2 y old): 10 children who remained caries-free, 10 who developed noncavitated caries, and 10 who developed cavitated caries. Saliva samples collected at baseline before caries onset were analyzed through 16S rRNA gene sequencing. The results of β diversity analysis showed a significant difference in salivary microbiome composition between children who remained caries-free and those who developed cavitated caries at 2 y old (analysis of similarities, Benjamini-Hochberg corrected, P = 0.042). The relative abundance of Prevotella nanceiensis, Leptotrichia sp. HMT 215, Prevotella melaninogenica, and Campylobacter concisus in children who remained caries-free was significantly higher than in children who developed cavitated caries (Wilcoxon rank sum test, P = 0.024, 0.040, 0.049, and 0.049, respectively). These taxa were also identified as biomarkers for children who remained caries-free (linear discriminant analysis effect size, linear discriminant analysis score = 3.69, 3.74, 3.53, and 3.46). A machine learning model based on these 4 species distinguished between 1-y-old children who did and did not develop cavitated caries at 2 y old, with an accuracy of 80%, sensitivity of 80%, and specificity of 80% (area under the curve, 0.8; 95% CI, 44.4 to 97.5). Our findings suggest that these salivary microbial biomarkers could assist in predicting future caries in caries-free 1-y-old children and, upon validation, are promising for development into an adjunctive tool for caries risk prediction for prevention and monitoring.

Investigation of putative roles of smoking-associated salivary microbiome alterations on carcinogenesis by integrative in silico analysis

Growing evidence suggests that cigarette smoking alters the salivary microbiome composition and affects the risk of various complex diseases including cancer. However, the potential role of the smoking-associated microbiome in cancer development remains unexplained. Here, the putative roles of smoking-related microbiome alterations in carcinogenesis were investigated by in silico analysis and suggested evidence can be further explored by experimental methodologies. The Disbiome database was used to extract smoking-associated microbial taxa in saliva and taxon set enrichment analysis (TSEA) was conducted to identify the gene sets associated with extracted microbial taxa. We further analyzed the expression profiles of identified genes by using RNA-sequencing data from TCGA and GTEx projects. Associations of the genes with smoking-related phenotypes in cancer datasets were analyzed to prioritize genes for their interplay between smoking-related microbiome and carcinogenesis. Thirty-eight microbial taxa associated with smoking were included in the TSEA and this revealed sixteen genes that were significantly associated with smoking-associated microbial taxa. All genes were found to be differentially expressed in at least one cancer dataset, yet the ELF3 and CTSH were the most common differentially expressed genes giving significant results for several cancer types. Moreover, C2CD3, CTSH, DSC3, ELF3, RHOT2, and WSB2 showed statistically significant associations with smoking-related phenotypes in cancer datasets. This study provides in silico evidence for the potential roles of the salivary microbiome on carcinogenesis. The results shed light on the importance of smoking cessation strategies for cancer management and interventions to stratify smokers for their risk of smoking-induced carcinogenesis.

Analysis of the oral microbiome during hormonal cycle and its alterations in menopausal women: the “AMICA” project

The maintenance of human health is dependent on a symbiotic relationship between humans and associated bacteria. The diversity and abundance of each habitat’s signature microbes vary widely among body areas and among them the oral microbiome plays a key role. Significant changes in the oral cavity, predominantly at salivary and periodontal level, have been associated with changes in estrogen levels. However, whether the oral microbiome is affected by hormonal level alterations is understudied. Hence the main objective pursued by AMICA project was to characterize the oral microbiome (saliva) in healthy women through: profiling studies using "omics" technologies (NMR-based metabolomics, targeted lipidomics by LC–MS, metagenomics by NGS); SinglePlex ELISA assays; glycosidase activity analyses and bioinformatic analysis. For this purpose, thirty-nine medically healthy women aged 26–77 years (19 with menstrual cycle and 20 in menopause) were recruited. Participants completed questionnaires assessing detailed medical and medication history and demographic characteristics. Plasmatic and salivary levels of sexual hormones were assessed (FSH, estradiol, LH and progesteron) at day 3 and 14 for women with menstrual cycle and only once for women in menopause. Salivary microbiome composition was assessed through meta-taxonomic 16S sequencing and overall, the salivary microbiome of most women remained relatively stable throughout the menstrual cycle and in menopause. Targeted lipidomics and untargeted metabolomics profiling were assessed through the use of LC–MS and NMR spectroscopy technologies, respectively and significant changes in terms of metabolites were identified in saliva of post-menopausal women in comparison to cycle. Moreover, glycosyl hydrolase activities were screened and showed that the β-D-hexosaminidase activity was the most present among those analyzed. Although this study has not identified significant alterations in the composition of the oral microbiome, multiomics analysis have revealed a strong correlation between 2-AG and α-mannosidase. In conclusion, the use of a multidisciplinary approach to investigate the oral microbiome of healthy women provided some indication about microbiome-derived predictive biomarkers that could be used in the future for developing new strategies to help to re-establish the correct hormonal balance in post-menopausal women.

Investigating changes in salivary microbiota due to dental treatment: A metagenomic analysis study for forensic purposes

The advent of next generation sequencing techniques as well as the existing traditional culture methods has enabled metagenomic studies on the usability of microbiomes for the forensic identification of individuals to gain momentum. However, before the utilization of microbiomes as a potential technique for real forensic case resolutions, it is necessary to understand the stability of the microbiota compositions in an individual’s biological samples and the factors responsible for their variations. In the present study, we compared the microbiota compositions present in the saliva of individuals with active dental caries before and after treatment from a forensic and clinical perspective using an approach based on the sequencing of all the variable regions (V1–V9) of the bacterial 16 S rRNA gene. For this purpose, 10 individuals were included in the study comprising of 8 individuals between the ages of 18–50 years with at least 3 deep dentin caries as patients and 2 healthy individuals without any dental or gingival diseases as controls. Saliva samples were collected from the patients at two timepoints, before and after treatment, as well as from the healthy individuals (before and after control) at an interval of 1 month. The collected 20 saliva samples were subjected to metagenomic analysis using the MinION device, which was developed by Oxford Nanopore Technologies (ONT Oxford, UK). Bioinformatic analyses were performed on the obtained data and the results were evaluated using statistical comparison methods and alpha/beta diversity analyses within the scope of the study objective. On evaluation using the distance metrics, it was observed that the microbial compositions in the saliva of individuals with active caries remained relatively stable after treatment. However, the relative abundance levels of bacteria of 28 genera and species showed statistically significant differences before and after treatment (p < 0.05). As a result, although the composition of salivary microbiome remained relatively stable after caries treatment, there were significant changes in many types of bacteria, especially at the species level, between the BT and AT samples. Our results provide a framework for further forensic and clinical investigations regarding the factors that affect human salivary microbiome diversity.

The Microbiome in Periodontitis and Diabetes.

ObjectivesTo perform a comprehensive and integrative review of the available literature on the potential changes in the microbiome of healthy and individuals with diabetes under periodontal health and disease.Materials and MethodsThe review was conducted by two independent reviewers. Indexed electronic databases (PubMed/Medline, Cochrane Library, Web of Science and Scopus) were searched, including articles published in English and dated from 5 years ago until December 2021. A manual search also was performed to identify co-related articles. Following the removal of duplicates and eligibility criteria, the articles were included in tables for analysis and described in the manuscript.ResultsAccording to this review, diabetes mellitus was associated with significant changes in the subgingival and salivary microbiome, either in its association with periodontitis or in cases of periodontal health. In addition to affecting microbial diversity in terms of taxonomy, metagenomic studies have shown that this endocrine disorder may also be directly related to increased pathogenicity in the oral microbiome.ConclusionAlthough the reviewed studies demonstrate important differences in the subgingival and salivary microbiome composition because of diabetes mellitus, further studies are needed to clarify the real effects of hyperglycemia on oral microbial profiles and support new diagnostic approaches and innovative treatments.

Composition and Diversity of Salivary Microbiome Affected by Sample Collection Method

Composition and Diversity of Salivary Microbiome Affected by Sample Collection Method

Dynamic Microbial Shifts and Functional Analysis of Saliva Microbial Communities with Caries Children

To observe the dynamic changes in the salivary microbiota of children with dental caries and those who were caries-free and to analyze the functional differences in the oral microecology of the two groups during the course of sugar metabolism and the synthesis and transport of multiple amino acids. Ten children with dental caries and 10 caries-free children were enrolled. We employed Illumina metagenomics technology to analyze the composition and function of salivary microbiome in children with and without caries. Six months later, PacBio single-molecule long-read sequencing technology was used to analyze the changes over time in the oral microbial communities of the two groups. We studied the patterns of change in the oral microbial communities under diseased or healthy conditions and attempted to offer a comprehensive interpretation of children's oral microbiota in terms of its composition and functions. The composition of the oral microbiota of children with or without dental caries changed significantly over time. At the phylum level, changing trends in the salivary microbial communities of children with dental caries were in line with those in caries-free children. In these microbial communities, increased proportions of Firmicutes and decreased proportions of Actinobacteria and Bacteroidetes were found in the two groups. At the genus level, however, the two groups showed significantly different changes of the salivary microbial communities. Upward trends in the abundance of Lactobacillus, Methylobacterium, and Megasphaera were found in the caries group, while the abundance of these genera in the caries-free group showed downward trends. At the species level, L. fermentum, L. gasseri, L. oris, S. downei, and some other species belonging to the genus Lactobacillus showed upward trends in the saliva of children with caries, while they consistently stayed at a relative low level of abundance in caries-free children. The abundance of S. gordonii and S. mutans decreased to a certain extent in children with dental caries, but the abundance of S. gordonii and S. mutans in caries-free children were always at a low level. Species such as S. mutans and C. gracilis were positively correlated to the sum of decayed, missing and filled teeth (dmft), while N. flavescens was negatively correlated to dmft. gltA, icd, and mqo, the key genes related to tricarboxylic acid (TCA) cycle, gudB, a glutamate synthesis-related gene, and argAB/C/J, arginine synthesis-related genes, were significantly increased in caries-free children. In addition, the abundance of the NADH dehydrogenase-related gene nuoB/C/D/E/H/I/J/K/L/M in the electron transport chain increased significantly in caries-free children. Dynamic changes were found in the oral microbiota of children with or without caries. The trends of microbial shifts over time were associated with the oral health status. Oxidative phosphorylation and the synthesis and transport of amino acids such as glutamate and arginine in the oral microecology were more active in caries-free children.

Salivary Microbial Dysbiosis Is Associated With Peri-Implantitis: A Case-Control Study in a Brazilian Population.

Background and ObjectivesThe aim of this study was to examine the salivary microbiome in healthy peri-implant sites and those with peri-implantitis.MethodsSaliva samples were collected from 21 participants with healthy peri-implant sites and 21 participants with peri-implantitis. The V4 hypervariable region of the 16S rRNA gene was sequenced using the Ion Torrent PGM System (Ion 318™ Chip v2 400). The NGS analysis and composition of the salivary microbiome were determined by taxonomy assignment. Downstream bioinformatic analyses were performed in QIIME (v 1.9.1).ResultsClinical differences according to peri-implant condition status were found. Alpha diversity metrics revealed that the bacterial communities of participants with healthy peri-implant sites tended to have a richer microbial composition than individuals with peri-implantitis. In terms of beta diversity, bleeding on probing (BoP) may influence the microbial diversity. However, no clear partitioning was noted between the salivary microbiome of volunteers with healthy peri-implant sites or volunteers with peri-implantitis. The highest relative abundance of Stenotrophomonas, Enterococcus and Leuconostoc genus, and Faecalibacterium prausnitzii, Haemophilus parainfluenzae, Prevotella copri, Bacteroides vulgatus, and Bacteroides stercoris bacterial species was found in participants with peri-implantitis when compared with those with healthy peri-implant sites.ConclusionDifferences in salivary microbiome composition were observed between patients with healthy peri-implant sites and those with peri-implantitis. BoP could affect the diversity (beta diversity) of the salivary microbiome.

Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari Population.

Background: Many studies have linked dysbiosis of the gut microbiome to the development of cardiovascular diseases (CVD). However, studies assessing the association between the salivary microbiome and CVD risk on a large cohort remain sparse. This study aims to identify whether a predictive salivary microbiome signature is associated with a high risk of developing CVD in the Qatari population.Methods: Saliva samples from 2,974 Qatar Genome Project (QGP) participants were collected from Qatar Biobank (QBB). Based on the CVD score, subjects were classified into low-risk (LR < 10) (n = 2491), moderate-risk (MR = 10–20) (n = 320) and high-risk (HR > 30) (n = 163). To assess the salivary microbiome (SM) composition, 16S-rDNA libraries were sequenced and analyzed using QIIME-pipeline. Machine Learning (ML) strategies were used to identify SM-based predictors of CVD risk.Results: Firmicutes and Bacteroidetes were the predominant phyla among all the subjects included. Linear Discriminant Analysis Effect Size (LEfSe) analysis revealed that Clostridiaceae and Capnocytophaga were the most significantly abundant genera in the LR group, while Lactobacillus and Rothia were significantly abundant in the HR group. ML based prediction models revealed that Desulfobulbus, Prevotella, and Tissierellaceae were the common predictors of increased risk to CVD.Conclusion: This study identified significant differences in the SM composition in HR and LR CVD subjects. This is the first study to apply ML-based prediction modeling using the SM to predict CVD in an Arab population. More studies are required to better understand the mechanisms of how those microbes contribute to CVD.

Relationship between Saliva and Sublingual Immunotherapy.

The demand for allergen specific immunotherapy (AIT), especially sublingual immunotherapy (SLIT), is increasing because of its efficacy in inducing clinical remission of allergic diseases and its low risk of side effects. Since not all patients that undergo SLIT demonstrate an improvement in allergic symptoms, the development of biomarkers to predict the outcome and adjuvants for SLIT is desired. Saliva is the first target with which tablets used in SLIT come into contact, and salivary pH, chemical properties or microbiome composition are reported to possibly be associated with the outcome of SLIT. Antibodies such as IgG4 and IgA not only in the serum but also in the saliva are increased after SLIT and may also be associated with the efficacy of SLIT. The development of the metagenomic sequencing technique makes it possible to determine the microbiome composition and ratio of each bacterium, and researchers can investigate the relationships between specific bacteria and the immune response. Some bacteria are reported to improve the SLIT outcome and have the potential to be used as biomarkers for the selection of patients and as adjuvants in SLIT. Here, we introduce biomarkers for SLIT and present recent findings regarding the relationship between saliva and SLIT.

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

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

Salivary Microbiome Diversity in Kuwaiti Adolescents with Varied Body Mass Index-A Pilot Study.

The potential role of the salivary microbiome in human diseases has increasingly been explored. The salivary microbiome has been characterized in several global populations, except the Arabian Gulf region. Hence, in this pilot study, we profiled the salivary microbiome of Kuwaiti adolescents with varied body mass indexes (BMI). The analyses of core microbiome composition showed Firmicutes, Bacteroidota, Proteobacteria, Patescibacteria, Fusobacteriota, Actinobacteriota, and Campylobacterota as the common phylum found in the Kuwaiti adolescent population. We also illustrated a diverse microbial community among the sampled individuals grouped according to their BMI. Notably, the overweight group was found with a higher number of distinct taxa than other groups. As such, the core microbiome composition was found to be significantly different (p-value < 0.001) across different BMI groups. Overall, this pilot investigation outlined the microbial diversity and suggested that changes in salivary microbiome composition in people with obese or overweight BMI might reflect their susceptibility to oral diseases.

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

ObjectiveStudies have shown that oral microbiota composition is altered in type 2 diabetes mellitus, implying that it is a potential biomarker for diabetes. This study aimed at constructing a noninvasive auxiliary diagnostic model for diabetes based on differences in the salivary microbial community. DesignSalivary microbiota from 24 treatment-naive type 2 diabetes mellitus patients and 21 healthy populations were detected through 16S rRNA gene sequencing, targeting the V3/V4 region using the MiSeq platform. Salivary microbiome diversity and composition were analyzed so as to establish a diagnostic model for type 2 diabetes. ResultsSalivary microbiome for treatment-naive type 2 diabetes mellitus patients was imbalanced with certain taxa, including Slackia, Mitsuokella, Abiotrophia, and Parascardovia that being significantly dominant, while the abundance of Moraxella was high in healthy controls. Diabetic patients exhibited varying levels of Prevotella nanceiensis and Prevotella melaninogenica which were negatively correlated with glycosylated hemoglobin and fasting blood glucose levels, as well as fasting blood glucose levels, respectively. Based on differences in salivary microbiome composition between diabetic and healthy groups, we developed a diagnostic model that can be used for the auxiliary diagnosis of type 2 diabetes mellitus with an accuracy of 80 %. ConclusionsThese findings elucidate on the differences in salivary microbiome compositions between type 2 diabetic and non-diabetic populations, and the diagnostic model provides a promising approach for the noninvasive auxiliary diagnosis of diabetes mellitus.

MICROBIOME DIVERSITY IN THE SALIVA RELATED ORAL AND SYSTEMIC DISEASES

This review aimed to evaluate findings related to the human normal salivary microbiomes, the presence of opportunist salivary microbiome concerning oral and systemic diseases, and the use of salivary microbiome metagenomic analysis. Method: This review accomplishes using PubMed, Science Direct, and Google scholar. After reading the titles and abstracts, 2.718 works of literature screens for this review, content analysis performs. Results: Human normal salivary microbiomes consist of yeast, gram-positive, and gramnegative bacteria. A commensal microbial community founds in healthy people. An opportunist microbial community establishes in unhealthy people. It is essential to note an association between the opportunist microbiome composition with the personal health condition. Specific opportunist microbiome relates to particular diseases, such as diabetes, respiratory diseases, cancer, autoimmune, and viral infections. Even is different results of the conventional method and the modern methods (metagenomic analysis), both approaches can determine the presence of specific opportunist salivary microbiome concerning certain systemic diseases. Conclusion: Salivary microbiome composition can be a biomarker for people's health conditions and various systemic diseases. Both conventional methods and the modern method can be used complementarily for biomarker determination.

Experimental Therapeutic Solutions for Behcet's Disease.

Behcet’s disease (BD) is a chronic systemic vasculitis with inflammation attacks that involve multiple organs. In addition to numerous mucocutaneous symptoms, notably recurrent oral and genital ulcers, ocular, articular, vascular, gastrointestinal, cardiac, and neurological system involvement can be observed. Mucocutaneous lesions are the primary symptom of the disease in most patients, and they usually occur before major organ involvement and other symptoms of the disease. Recognizing the disease’s mucocutaneous lesions is very important to diagnose at an early stage, control with appropriate treatment and close follow-up, and prevent major organ involvement. Genome-wide association studies (GWAS) in recent years have confirmed that HLA-B*51 is the most significant genetic predisposing factor. The majority of gene polymorphisms have been detected in molecules that respond to microorganisms and genes encoding cytokines and adhesion molecules. The infectious agent S. sanguinis -commonly found in the oral mucosa of patients with BD- or the differences in the salivary or intestinal microbiome composition can trigger innate immune-mediated inflammation sustained by acquired or adaptive immune responses. In antigen-presenting cells (APCs), epistatic interactions between HLA-B*51 and endoplasmic reticulum aminopeptidase 1 (ERAP1) variants lead to the disruption of T-cell homeostasis, especially the activation of Type1 T-helper and Th17 pathway and suppression of regulatory T-cells. Recent developments to clarify the disease’s etiopathogenesis provided us with a better understanding of the mechanism of action of the relatively old drugs while opening a way for many new treatment methods. Apremilast has become an important option in the treatment of mucocutaneous symptoms with its high efficacy and safety. The disease increases the mortality rate, especially in young male patients. New treatments, especially anti-TNF-α agents, have provided significant progress and decreased the mortality rates with their rapid effect and high efficacy in patients with severe organ involvement and resistance to traditional immunosuppressive and immunomodulatory therapies. The use of IL-1, IL-6, IL-17, IL-12/IL-23 antagonists in different organ involvement has gradually increased, and the quality of life has significantly improved in many patients.

Salivary microbiome composition changes after bariatric surgery

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

Low levels of salivary metals, oral microbiome composition and dental decay

Salivary microbiome composition can change following exposure to environmental toxicants, e.g., heavy metals. We hypothesized that levels of salivary nutrients and metals would correlate with salivary microbiome composition and be associated with dental decay. Here we assess the salivary concentrations of 5 essential minerals (cobalt, copper, manganese, molybdenum, and zinc), 4 metals with some evidence of normal physiological function (chromium, nickel, tungsten, and vanadium), and 12 with known toxicity (antimony, arsenic, barium, beryllium, cadmium, cesium, lead, mercury, platinum, thallium, tin, and uranium), and their associations with salivary microbiome composition and dental decay in 61 children and adults. 16 metals were detected in 54% of participants; 8 were found in all. Marked differences in salivary bacterial taxa were associated with levels of antimony, arsenic, and mercury, after adjusting for multiple testing. Further, antimony levels were associated with the presence of decayed teeth. Thus, salivary metal levels, even at low concentrations, may impact oral health.

Oral Microbiota Display Profound Differential Metabolic Kinetics and Community Shifts upon Incubation with Sucrose, Trehalose, Kojibiose, and Xylitol.

This study compares the metabolic properties of kojibiose, trehalose, sucrose, and xylitol upon incubation with representative oral bacteria as monocultures or synthetic communities or with human salivary bacteria in a defined medium. Compared to sucrose and trehalose, kojibiose resisted metabolism during a 48-h incubation with monocultures, except for Actinomyces viscosus Incubations with Lactobacillus-based communities, as well as salivary bacteria, displayed kojibiose metabolism, yet to a lesser extent than sucrose and trehalose. Concurring with our in vitro findings, screening for carbohydrate-active enzymes revealed that only Lactobacillus spp. and A. viscosus possess enzymes from glycohydrolase (GH) families GH65 and GH15, respectively, which are associated with kojibiose metabolism. Donor-dependent differences in salivary microbiome composition were noted, and differences in pH drop during incubation indicated different rates of sugar metabolism. However, functional analysis indicated that lactate, acetate, and formate evenly dominated the metabolic profile for all sugars except for xylitol. 16S rRNA gene sequencing analysis and α-diversity markers revealed that a significant shift of the microbiome community by sugars was more pronounced in sucrose and trehalose than in kojibiose and xylitol. In Streptococcus spp., a taxon linked to cariogenesis dominated in sucrose (mean ± standard deviation, 91.8 ± 6.4%) and trehalose (55.9 ± 38.6%), representing a high diversity loss. In contrast, Streptococcus (5.1 ± 3.7%) was less abundant in kojibiose, which instead was dominated by Veillonella (26.8 ± 19.6%), while for xylitol, Neisseria (29.4 ± 19.1%) was most abundant. Overall, kojibiose and xylitol incubations stimulated cariogenic species less yet closely maintained an abundance of key phyla and genera of the salivary microbiome, suggesting that kojibiose has low cariogenic properties.IMPORTANCE This study provides a detailed scientific insight on the metabolism of a rare disaccharide, kojibiose, whose mass production has recently been made possible. While the resistance of kojibiose was established with monocultures, delayed utilization of kojibiose was observed with communities containing lactobacilli and A. viscosus as well as with complex communities of bacteria from human saliva. Kojibiose is, therefore, less metabolizable than sucrose and trehalose. Moreover, although conventional sugars cause distinct shifts in salivary microbial communities, our study has revealed that kojibiose is able to closely maintain the salivary microbiome composition, suggesting its low cariogenic properties. This study furthermore underscores the importance and relevance of microbial culture and ex vivo mixed cultures to study cariogenicity and substrate utilization; this is in sharp contrast with tests that solely rely on monocultures such as Streptococcus mutans, which clearly fail to capture complex interactions between oral microbiota.