Histological assessment and gene expression analysis of intra-oral soft tissue graft donor sites.

AIM: To determine the structural and gene expression features of different intra-oral soft tissue donor sites (i.e., anterior palate, posterior palate, maxillary tuberosity and retromolar pad). MATERIALS AND METHODS: Standardized mucosal tissue punch biopsies were collected from at least one donor site per subject. Histological processing was performed to determine tissue morphometry and quantify collagen composition. Site-specific gene distribution was mapped using targeted gene expression analysis and validated using real time polymerase chain reaction (qPCR). RESULTS: A total of 50 samples from 37 subjects were harvested. Epithelial thickness did not differ between sites. However, lamina propria was thicker in the maxillary tuberosity (2.55 ± 0.92 mm) and retromolar pad (1.98 ± 0.71 mm) than in the lateral palate. Type I collagen was the predominant structural protein in the lamina propria (75.06%-80.21%). Genes involving collagen maturation and extracellular matrix regulation were highly expressed in the maxillary tuberosity and retromolar pad, while lipogenesis-associated genes were markedly expressed in the lateral palate. The retromolar pad showed the most distinct gene expression profile, and the anterior and posterior palate displayed similar transcription profiles. CONCLUSIONS: Tissue samples harvested from the anterior and posterior palate differed morphologically from those from the maxillary tuberosity and retromolar pad. Each intra-oral site showed a unique gene expression profile, which might impact their biological behaviour and outcomes of soft tissue augmentation procedures.

COVID-19 associated oral and oropharyngeal microbiome: Systematic review and meta-analysis.

Three years into the coronavirus disease 2019 (COVID-19) pandemic, there are still growing concerns with the emergence of different variants, unknown long- and short-term effects of the virus, and potential biological mechanisms underlying etiopathogenesis and increased risk for morbidity and mortality. The role of the microbiome in human physiology and the initiation and progression of several oral and systemic diseases have been actively studied in the past decade. With the proof of viral transmission, carriage, and a potential role in etiopathogenesis, saliva and the oral environment have been a focus of COVID-19 research beyond diagnostic purposes. The oral environment hosts diverse microbial communities and contributes to human oral and systemic health. Several investigations have identified disruptions in the oral microbiome in COVID-19 patients. However, all these studies are cross-sectional in nature and present heterogeneity in study design, techniques, and analysis. Therefore, in this undertaking, we (a) systematically reviewed the current literature associating COVID-19 with changes in the microbiome; (b) performed a re-analysis of publicly available data as a means to standardize the analysis, and (c) reported alterations in the microbial characteristics in COVID-19 patients compared to negative controls. Overall, we identified that COVID-19 is associated with oral microbial dysbiosis with significant reduction in diversity. However, alterations in specific bacterial members differed across the study. Re-analysis from our pipeline shed light on Neisseria as the potential key microbial member associated with COVID-19.

The role of the oral microbiome in smoking-related cardiovascular risk: a review of the literature exploring mechanisms and pathways.

Cardiovascular disease is a leading cause of morbidity and mortality. Oral health is associated with smoking and cardiovascular outcomes, but there are gaps in knowledge of many mechanisms connecting smoking to cardiovascular risk. Therefore, the aim of this review is to synthesize literature on smoking and the oral microbiome, and smoking and cardiovascular risk/disease, respectively. A secondary aim is to identify common associations between the oral microbiome and cardiovascular risk/disease to smoking, respectively, to identify potential shared oral microbiome-associated mechanisms. We identified several oral bacteria across varying studies that were associated with smoking. Atopobium, Gemella, Megasphaera, Mycoplasma, Porphyromonas, Prevotella, Rothia, Treponema, and Veillonella were increased, while Bergeyella, Haemophilus, Lautropia, and Neisseria were decreased in the oral microbiome of smokers versus non-smokers. Several bacteria that were increased in the oral microbiome of smokers were also positively associated with cardiovascular outcomes including Porphyromonas, Prevotella, Treponema, and Veillonella. We review possible mechanisms that may link the oral microbiome to smoking and cardiovascular risk including inflammation, modulation of amino acids and lipids, and nitric oxide modulation. Our hope is this review will inform future research targeting the microbiome and smoking-related cardiovascular disease so possible microbial targets for cardiovascular risk reduction can be identified.

Biome-microbiome interactions in peri-implantitis: A pilot investigation.

BACKGROUND: Dental implants replace missing teeth in at least 100 million people, yet over one million implants fail every year due to peri-implantitis, a bacterially induced inflammatory disease. Our ability to treat peri-implantitis is hampered by a paucity of information on host-microbiome interactions that underlie the disease. Here, we present the first open-ended characterization of transcriptional events at the mucosal-microbial interface in the peri-implant crevice. METHODS: We simultaneously sequenced microbial and human mRNA from five pairs of healthy and diseased implants from the same patient and used graph theoretics to examine correlations between microbial and host gene expression in the peri-implant crevice. RESULTS: We identified a transcriptionally active peri-implant microbiome surrounding healthy implants. Microbial genes encoding phenylalanine, tyrosine, and tryptophan biosynthesis, cysteine, methionine, arginine, proline, and histidine metabolism correlated to human genes encoding cell development, metabolism, morphogenesis, adhesion, gap junctions, cell-cell signaling, and immunoinflammatory pathways, suggesting a role for commensals in protecting epithelial integrity. In disease, we found 4- to 200-fold upregulation in microbial genes encoding biofilm thickness, heme transport and utilization, and Gram-negative cell membrane synthesis. These genes correlated with mucosal zinc finger proteins, apoptosis, membrane transport, inflammation, and cell-cell communication. CONCLUSIONS: Within the limitations of a small sample size, our data suggest that microbial dysbiosis in the peri-implant sulcus might promote abandonment of host-bacterial transactions that dictate health and instead drive a move towards chronic programming of a non-healing wound.

An in vitro model for studies of attenuation of antibiotic-inhibited growth of Aggregatibacter actinomycetemcomitans Y4 by polyamines.

Polyamines are ubiquitous polycationic molecules that are present in all prokaryotic and eukaryotic cells, and they serve as important modulators of cell growth, stress, and cell proliferation. Polyamines are present at high concentrations in the periodontal pocket and could potentially affect the stress response of periodontal bacteria to antibiotics. The effects of polyamines on inhibition of growth by amoxicillin (AMX), azithromycin (AZM), and doxycycline (DOX) were investigated with the Y4 strain of Aggregatibacter actinomycetemcomitans (Aa). Bacteria were grown in brain heart infusion broth under the following conditions: (1) Aa only, (2) Aa + polyamine mix (1 mM putrescine, 0.4 mM spermidine, and 0.4 mM spermine), (3) Aa + antibiotic, and (4) Aa + antibiotic + polyamines. Growth curve analysis, minimal inhibitory concentration determination, and transcriptomic studies were conducted. The presence of exogenous polyamines produced a small, but significant increase in Aa growth, and polyamines attenuated the inhibitory effects of AMX, AZM, and DOX on growth. Transcriptomic analysis revealed that polyamines upregulate expression of ribosomal biogenesis proteins and small subunits, attenuate the bacterial stress response to antibiotics, and modulate bacterial nutritional pathways in a manner that could potentially increase the virulence of Aa. In summary, the polyamine-rich environment found in periodontal pockets appears to protect Aa and reduce its susceptibility to several antimicrobial agents in this in vitro model.

Waistline to the gumline: Relationship between obesity and periodontal disease-biological and management considerations.

Obesity is a pandemic and periodontitis is the sixth most prevalent disease in the world. These two noncommunicable diseases share several risk determinants. Epidemiologic evidence from the last 2 decades has established an increase in periodontitis prevalence in obese and overweight individuals. Biologic mechanisms potentially linking obesity and periodontal disease are adiposity-associated hyperinflammation, microbial dysbiosis, altered immune response, specific genetic polymorphisms, and increased stress. However, because of the lack of longitudinal interventional studies and randomized clinical trials, there is insufficient evidence to determine the cause-effect relationship between these two diseases. Despite this, the negative impact of obesity on oral health is well established. Several logistic and physiologic complications are associated with treating obese patients in a dental setting, and it requires an interprofessional team approach. Oral health care professionals need to be aware of the specific management considerations while rendering for this cohort, including modified practice facility and equipment, tailored supportive periodontal therapy, and heightened precaution during conscious sedation and surgical procedures.

Anna Karenina and the subgingival microbiome associated with periodontitis.

BACKGROUND: Although localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP), and chronic periodontitis (CP) are microbially driven diseases, our inability to separate disease-specific associations from those common to all three forms of periodontitis has hampered biomarker discovery. Therefore, we aimed to map the genomic content of, and the biological pathways encoded by, the microbiomes associated with these clinical phenotypes. We also estimated the extent to which these biomes are governed by the Anna Karenina principle (AKP), which states that eubiotic communities are similar between individuals while disease-associated communities are highly individualized. METHODS: We collected subgingival plaque from 25 periodontally healthy individuals and diseased sites of 59 subjects with stage 3 periodontitis and used shotgun metagenomics to characterize the aggregate of bacterial genes. RESULTS: Beta-dispersion metrics demonstrated that AKP was most evident in CP, followed by GAP and LAP. We discovered broad dysbiotic signatures spanning the three phenotypes, with over-representation of pathways that facilitate life in an oxygen-poor, protein- and heme-rich, pro-oxidant environment and enhance capacity for attachment and biofilm formation. Phenotype-specific indicators were more readily evident in LAP microbiome than GAP or CP. Genes that enable acetate-scavenging lifestyle, utilization of alternative nutritional sources, oxidative and nitrosative stress responses, and siderophore production were unique to LAP. An attenuation of virulence-related functionalities and stress response from LAP to GAP to CP was apparent. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease. CONCLUSION: Within the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease, or an artifact induced by cross-sectional study designs. Further studies on phenotype-specific microbial genes are warranted to explicate their role in disease etiology. Video Abstract.

Probing periodontal microbial dark matter using metataxonomics and metagenomics.

Our view of the periodontal microbial community has been shaped by a century or more of cultivation-based and microscopic investigations. While these studies firmly established the infection-mediated etiology of periodontal diseases, it was apparent from the very early days that periodontal microbiology suffered from what Staley and Konopka described as the "great plate count anomaly", in that these culturable bacteria were only a minor part of what was visible under the microscope. For nearly a century, much effort has been devoted to finding the right tools to investigate this uncultivated majority, also known as "microbial dark matter". The discovery that DNA was an effective tool to "see" microbial dark matter was a significant breakthrough in environmental microbiology, and oral microbiologists were among the earliest to capitalize on these advances. By identifying the order in which nucleotides are arranged in a stretch of DNA (DNA sequencing) and creating a repository of these sequences, sequence databases were created. Computational tools that used probability-driven analysis of these sequences enabled the discovery of new and unsuspected species and ascribed novel functions to these species. This review will trace the development of DNA sequencing as a quantitative, open-ended, comprehensive approach to characterize microbial communities in their native environments, and explore how this technology has shifted traditional dogmas on how the oral microbiome promotes health and its role in disease causation and perpetuation.

Adverse effects of electronic cigarettes on the disease-naive oral microbiome.

Six percent of Americans, including 3 million high schoolers, use e-cigarettes, which contain potentially toxic substances, volatile organic compounds, and metals. We present the first human study on the effects of e-cigarette exposure in the oral cavity. By interrogating both immunoinflammatory responses and microbial functional dynamics, we discovered pathogen overrepresentation, higher virulence signatures, and a brisk proinflammatory signal in clinically healthy e-cigarette users, equivalent to patients with severe periodontitis. Using RNA sequencing and confocal and electron microscopy to validate these findings, we demonstrate that the carbon-rich glycol/glycerol vehicle is an important catalyst in transforming biofilm architecture within 24 hours of exposure. Last, a machine-learning classifier trained on the metagenomic signatures of e-cigarettes identified as e-cigarette users both those individuals who used e-cigarettes to quit smoking, and those who use both e-cigarettes and cigarettes. The present study questions the safety of e-cigarettes and the harm reduction narrative promoted by advertising campaigns.

Current State of and Future Opportunities for Prediction in Microbiome Research: Report from the Mid-Atlantic Microbiome Meet-up in Baltimore on 9 January 2019.

Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research.

The making of a miscreant: tobacco smoke and the creation of pathogen-rich biofilms.

We have previously reported that oral biofilms in clinically healthy smokers are pathogen-rich, and that this enrichment occurs within 24 h of biofilm formation. The present investigation aimed to identify a mechanism by which smoking creates this altered community structure. By combining in vitro microbial-mucosal interface models of commensal (consisting of Streptococcus oralis, Streptococcus sanguis, Streptococcus mitis, Actinomyces naeslundii, Neisseria mucosa and Veillonella parvula) and pathogen-rich (comprising S.oralis, S.sanguis, S.mitis, A.naeslundii, N.mucosa and V.parvula, Fusobacterium nucleatum, Porphyromonas gingivalis, Filifactor alocis, Dialister pneumosintes, Selenonomas sputigena, Selenominas noxia, Catonella morbi, Parvimonas micra and Tannerella forsythia) communities with metatranscriptomics, targeted proteomics and fluorescent microscopy, we demonstrate that smoke exposure significantly downregulates essential metabolic functions within commensal biofilms, while significantly increasing expression of virulence genes, notably lipopolysaccharide (LPS), flagella and capsule synthesis. By contrast, in pathogen-rich biofilms several metabolic pathways were over-expressed in response to smoke exposure. Under smoke-rich conditions, epithelial cells mounted an early and amplified pro-inflammatory and oxidative stress response to these virulence-enhanced commensal biofilms, and a muted early response to pathogen-rich biofilms. Commensal biofilms also demonstrated early and widespread cell death. Similar results were observed when smoke-free epithelial cells were challenged with smoke-conditioned biofilms, but not vice versa. In conclusion, our data suggest that smoke-induced transcriptional shifts in commensal biofilms triggers a florid pro-inflammatory response, leading to early commensal death, which may preclude niche saturation by these beneficial organisms. The cytokine-rich, pro-oxidant, anaerobic environment sustains inflammophilic bacteria, and, in the absence of commensal antagonism, may promote the creation of pathogen-rich biofilms in smokers.

A tale of two risks: smoking, diabetes and the subgingival microbiome.

Although smoking and diabetes have been established as the only two risk factors for periodontitis, their individual and synergistic impacts on the periodontal microbiome are not well studied. The present investigation analyzed 2.7 million 16S sequences from 175 non-smoking normoglycemic individuals (controls), smokers, diabetics and diabetic smokers with periodontitis as well as periodontally healthy controls, smokers and diabetics to assess subgingival bacterial biodiversity and co-occurrence patterns. The microbial signatures of periodontally healthy smokers, but not diabetics, were highly aligned with the disease-associated microbiomes of their respective cohorts. Diabetics were dominated by species belonging to Fusobacterium, Parvimonas, Peptostreptococcus, Gemella, Streptococcus, Leptotrichia, Filifactor, Veillonella, TM7 and Terrahemophilus. These microbiomes exhibited significant clustering based on HbA1c levels (pre-diabetic (<6.5%), diabetic (6.5-9.9%), diabetics >10%). Smokers with periodontitis evidenced a robust core microbiome (species identified in at least 80% of individuals) dominated by anaerobes, with inter-individual differences attributable largely to the 'rare biosphere'. Diabetics and diabetic smokers, on the other hand, were microbially heterogeneous and enriched for facultative species. In smokers, microbial co-occurrence networks were sparse and predominantly congeneric, while robust inter-generic networks were observed in diabetics and diabetic smokers. Smoking and hyperglycemia impact the subgingival microbiome in distinct ways, and when these perturbations intersect, their synergistic effect is greater than what would be expected from the sum of each effect separately. Thus, this study underscores the importance of early intervention strategies in maintaining health-compatible microbiomes in high-risk individuals, as well as the need to personalize these interventions based on the environmental perturbation.

Comparative metagenomics reveals taxonomically idiosyncratic yet functionally congruent communities in periodontitis.

The phylogenetic characteristics of microbial communities associated with periodontitis have been well studied, however, little is known about the functional endowments of this ecosystem. The present study examined 73 microbial assemblages from 25 individuals with generalized chronic periodontitis and 25 periodontally healthy individuals using whole genome shotgun sequencing. Core metabolic networks were computed from taxa and genes identified in at least 80% of individuals in each group. 50% of genes and species identified in health formed part of the core microbiome, while the disease-associated core microbiome contained 33% of genes and only 1% of taxa. Clinically healthy sites in individuals with periodontitis were more aligned with sites with disease than with health. 68% of the health-associated metagenome was dedicated to energy utilization through oxidative pathways, while in disease; fermentation and methanogenesis were predominant energy transfer mechanisms. Expanded functionality was observed in periodontitis, with unique- or over-representation of genes encoding for fermentation, antibiotic resistance, detoxification stress, adhesion, invasion and intracellular resistance, proteolysis, quorum sensing, Type III/IV secretion systems, phages and toxins in the disease-associated core microbiome. However, different species or consortia contributed to these functions in each individual. Several genes, but not species, demonstrated robust discriminating power between health and disease.