High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis

Diabetic Rats Induced Using a High-Fat Diet and Low-Dose Streptozotocin Treatment Exhibit Gut Microbiota Dysbiosis and Osteoporotic Bone Pathologies

Type 2 diabetes mellitus (T2DM) presents a challenge for individuals today, affecting their health and life quality. Besides its known complications, T2DM has been found to contribute to bone/mineral abnormalities, thereby increasing the vulnerability to bone fragility/fractures. However, there is still a need for appropriate diagnostic approaches and targeted medications to address T2DM-associated bone diseases. This study aims to investigate the relationship between changes in gut microbiota, T2DM, and osteoporosis. To explore this, a T2DM rat model was induced by combining a high-fat diet and low-dose streptozotocin treatment. Our findings reveal that T2DM rats have lower bone mass and reduced levels of bone turnover markers compared to control rats. We also observe significant alterations in gut microbiota in T2DM rats, characterized by a higher relative abundance of Firmicutes (F) and Proteobacteria (P), but a lower relative abundance of Bacteroidetes (B) at the phylum level. Further analysis indicates a correlation between the F/B ratio and bone turnover levels, as well as between the B/P ratio and HbA1c levels. Additionally, at the genus level, we observe an inverse correlation in the relative abundance of Lachnospiraceae. These findings show promise for the development of new strategies to diagnose and treat T2DM-associated bone diseases.

Community dynamics of subgingival microbiome in periodontitis and targets for microbiome modulation therapy

The microbial aetiology for periodontitis has been widely studied and deciphered for more than a century. The evolving and changing concepts about periodontal microbiology can be attributed to continuously developing laboratory techniques. The current sequencing platforms have not only expanded the catalog of periodontal pathogens but have also facilitated the understanding of functional interactions of the ecological framework. However, the translation of this new knowledge to advance periodontal therapeutics is minimal. We contend that novel clinical interventions directed beyond conventional therapies need to be emphasized. A clear understanding of the structural and functional dynamics of subgingival microbiota is a pre-requisite for developing any microbiome-based interventions for applications in periodontal health care. In this review, we discuss the 16 s-rRNA gene sequencing-based knowledge of the subgingival microbial community structure, its interactions and functions, and our perspective on the potential to engineer it for periodontal therapeutics. Harnessing this next-generation sequencing-based knowledge, microbiome modulation therapies are poised to change microbiome therapeutics' face.

Comparative analysis of subgingival microbiota in patients with mild, moderate, and severe chronic periodontitis

In this study, we explored the suspected pathogens of chronic periodontitis at different stages of occurrence and development. We collected 100 gingival crevicular fluid samples, 27, 27, and 26 from patients with mild, moderate, and severe chronic periodontitis, respectively, and 20 from healthy individuals. Pathogens were detected using a 16S rRNA metagenomic approach. Quantitative Insights in Microbial Ecology, Mothur, and other software were used to analyze the original data, draw relative abundance histograms and heat maps, and calculate flora abundance and diversity indexes. We identified 429 operational taxonomic units, covering 13 phyla, 20 classes, 32 orders, 66 families, and 123 genera from the four groups of samples. Each group showed microbial diversity, and the number of new species of bacterial flora in the gingival crevicular fluid samples gradually increased from the healthy to the severe chronic periodontitis group. There was a significant difference in the relative abundance of the core flora at the phylum, class, order, family, and genus classification levels. Our data indicated a certain correlation between the changes in the subgingival microbial structure and the occurrence and development of chronic periodontitis, which might be able to provide a reference for the diagnosis, treatment and prevention of chronic periodontitis.

Differential analysis of culturable and unculturable subgingival target microorganisms according to the stages of periodontitis

OBJECTIVES

Culturable and unculturable microorganisms have been associated with periodontitis. Their differential proportions and composition have not been evaluated by their severity and complexity defined by stages in the 2018 AAP-EEP classification.

METHODS

One hundred eighty subgingival biofilm samples were collected in Spain and Colombia from subjects categorized as health/gingivitis: periodontitis stages I/II periodontitis stages III/IV. Target culturable microorganisms (Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Tannerella forsythia, Treponema denticola, and Eubacterium nodatum) and target unculturable microorganisms (Filifactor alocis, Eubacterium saphenum, Eubacterium brachy, Desulfobulbus oralis) were evaluated by quantitative PCR analysis. In addition, their differences and association with periodontal status were analyzed by ANCOVA and logistic regression models once adjusted to age, current smoking, and country.

RESULTS

P. gingivalis was significantly associated with periodontitis stages I/II, OR 2.44 (CI 95% 1.08-5.47) and stages III/V, OR 6.43 (CI 95% 2.43-16.9). T forsythia, OR 7.53 (CI 95% 2.07-27.4); D. oralis, OR 5.99 (CI 95% 2.71-13.23); F. alocis, OR 10.9 (CI 95% 4.56-23.2); E. brachy, 3.57 (CI 95% 1.40-9.11); and E. saphenum, 4.85 (CI 95% 1.99-11.7) were significantly associated only with stages III/IV periodontitis. P. gingivalis evidenced significant differences with the increase in the severity of the periodontal lesion: 2.97 colony forming unit (CFU)/μL (CI 95% 2.32-3.54) health/gingivitis, and 4.66 CFU/μL (CI 95% 4.03-5.30) and 5.90 CFU/μL (CI 95% 5.20-6.48) in stages I/II and III/IV respectively (p < 0.0001). Unculturable microorganisms only evidenced differences in concentration in stages III/IV compared with health-gingivitis (p ≤ 0.001).

CONCLUSION

Culturable and unculturable are strongly associated with stages III/IV periodontitis. Classic culturable microorganisms are more sensitive to differentiate between stages of periodontitis in the quantitative analysis.

CLINICAL RELEVANCE

Future interventional studies of periodontal disease should include Filifactor alocis, Eubacterium saphenum, Eubacterium brachy, and Desulfobulbus oralis as possible markers of therapy response and as indicators of progressive disease.

Newly identified pathogens in periodontitis: evidence from an association and an elimination study

We assessed the level of evidence for the presence of new periodontal pathogens by (i) comparing the occurrence of non-classical periodontal taxa between healthy vs. periodontitis patients (Association study); (ii) assessing the modifications in the prevalence and levels of these species after treatments (Elimination study). In the Association study, we compared the prevalence and levels of 39 novel bacterial species between periodontally healthy and periodontitis patients. In the Elimination study, we analyzed samples from periodontitis patients assigned to receive scaling and root planing alone or with metronidazole+ amoxicillin TID/ 14 days. Levels of 79 bacterial species (39 novel and 40 classic) were assessed at baseline, 3 and 12 months post-therapy. All samples were analyzed using Checkerboard DNA-DNA hybridization. Out of the 39 novel species evaluated, eight were categorized as having strong and four as having moderate association with periodontitis. Our findings suggest strong evidence supporting Lancefieldella rimae, Cronobacter sakazakii, Pluralibacter gergoviae, Enterococcus faecalis, Eubacterium limosum, Filifactor alocis, Haemophilus influenzae, and Staphylococcus warneri, and moderate evidence supporting Escherichia coli, Fusobacterium necrophorum, Spiroplasma ixodetis, and Staphylococcus aureus as periodontal pathogens. These findings contribute to a better understanding of the etiology of periodontitis and may guide future diagnostic and interventional studies.

The oral microbiota is a reservoir for antimicrobial resistance: resistome and phenotypic resistance characteristics of oral biofilm in health, caries, and periodontitis

BACKGROUND

Antimicrobial resistance (AMR) is an ever-growing threat to modern medicine and, according to the latest reports, it causes nearly twice as many deaths globally as AIDS or malaria. Elucidating reservoirs and dissemination routes of antimicrobial resistance genes (ARGs) are essential in fighting AMR. Human commensals represent an important reservoir, which is underexplored for the oral microbiota. Here, we set out to investigate the resistome and phenotypic resistance of oral biofilm microbiota from 179 orally healthy (H), caries active (C), and periodontally diseased (P) individuals (TRN: DRKS00013119, Registration date: 22.10.2022). The samples were analysed using shotgun metagenomic sequencing combined, for the first time, with culture technique. A selection of 997 isolates was tested for resistance to relevant antibiotics.

RESULTS

The shotgun metagenomics sequencing resulted in 2,069,295,923 reads classified into 4856 species-level OTUs. PERMANOVA analysis of beta-diversity revealed significant differences between the groups regarding their microbiota composition and their ARG profile. The samples were clustered into three ecotypes based on their microbial composition. The bacterial composition of H and C samples greatly overlapped and was based on ecotypes 1 and 2 whereas ecotype 3 was only detected in periodontitis. We found 64 ARGs conveying resistance to 36 antibiotics, particularly to tetracycline, macrolide-lincosamide-streptogramin, and beta-lactam antibiotics, and a correspondingly high prevalence of phenotypic resistance. Based on the microbiota composition, these ARGs cluster in different resistotypes, and a higher prevalence is found in healthy and caries active than in periodontally diseased individuals. There was a significant association between the resistotypes and the ecotypes. Although numerous associations were found between specific antibiotic resistance and bacterial taxa, only a few taxa showed matching associations with both genotypic and phenotypic analyses.

CONCLUSIONS

Our findings show the importance of the oral microbiota from different niches within the oral cavity as a reservoir for antibiotic resistance. Additionally, the present study showed the need for using more than one method to reveal antibiotic resistance within the total oral biofilm, as a clear mismatch between the shotgun metagenomics method and the phenotypic resistance characterization was shown.

Pursuing new periodontal pathogens with an improved RNA-oligonucleotide quantification technique (ROQT)

OBJECTIVE

The aim of this study was to optimize the sensitivity, specificity and cost-effectiveness of the RNA-Oligonucleotide Quantification Technique (ROQT) in order to identify periodontal pathogens that remain unrecognized or uncultured in the oral microbiome.

DESIGN

Total nucleic acids (TNA) were extracted from subgingival biofilm samples using an automated process. RNA, DNA and Locked Nucleic Acid (LNA) digoxigenin-labeled oligonucleotide probes targeting 5 cultivated/named species and 16 uncultivated or unnamed bacterial taxa were synthesized. Probe specificity was determined by targeting 96 oral bacterial species; sensitivity was assessed using serial dilutions of reference bacterial strains. Different stringency temperatures were compared and new standards were tested. The tested conditions were evaluated analyzing samples from periodontally healthy individuals, and patients with moderate or severe periodontitis.

RESULTS

The automated extraction method at 63⁰C along with LNA-oligunucleotides probes, and use of reverse RNA sequences for standards yielded stronger signals without cross-reactions. In the pilot clinical study, the most commonly detected uncultivated/unrecognized species were Selenomonas sp. HMT 134, Prevotella sp. HMT 306, Desulfobulbus sp. HMT 041, Synergistetes sp. HMT 360 and Bacteroidetes HMT 274. In the cultivated segment of the microbiota, the most abundant taxa were T. forsythia HMT 613 and Fretibacterium fastidiosum (formerly Synergistetes) HMT 363.

CONCLUSIONS

In general, samples from severe patients had the greatest levels of organisms. Classic (T. forsythia, P. gingivalis) and newly proposed (F. alocis and Desulfobulbus sp. HMT 041) pathogens were present in greater amounts in samples from severe periodontitis sites, followed by moderate periodontitis sites.

Suspension of oral hygiene practices highlights key bacterial shifts in saliva, tongue, and tooth plaque during gingival inflammation and resolution

Experimentally induced gingivitis is associated with inflammatory and microbiological changes in an otherwise healthy subject, demonstrating the impacts of discontinuing oral hygiene routines. Understanding the bacterial dynamics during the induction and resolution of gingival inflammation will aid in the development of bacterial prognostic tests and probiotics for severe oral disease. We profiled the bacterial community in 15 healthy subjects who suspended all oral-hygiene practices for three weeks. Saliva, tongue, subgingival, and supragingival plaque samples were collected over seven weeks and showed a return to community baseline after oral hygiene practices were resumed. Stronger temporal changes in subgingival and supragingival plaque suggest these sample types may be preferred over saliva or tongue plaque for future prognostics. Taxonomic groups spanning ten phyla demonstrated consistent abundance shifts, including a significant decrease in Streptococcus, Neisseria, and Actinomyces populations, and an increase in Prevotella, Fusobacterium, and Porphyromonas populations. With four distinct oral sites surveyed and results mapped to the Human Oral Microbiome Database reference set, this work provides a comprehensive taxonomic catalog of the bacterial shifts observed during the onset and resolution of gingival inflammation.

HiPerMAb: a tool for judging the potential of small sample size biomarker pilot studies

Common statistical approaches are not designed to deal with so-called "short fat data" in biomarker pilot studies, where the number of biomarker candidates exceeds the sample size by magnitudes. High-throughput technologies for omics data enable the measurement of ten thousands and more biomarker candidates for specific diseases or states of a disease. Due to the limited availability of study participants, ethical reasons and high costs for sample processing and analysis researchers often prefer to start with a small sample size pilot study in order to judge the potential of finding biomarkers that enable - usually in combination - a sufficiently reliable classification of the disease state under consideration. We developed a user-friendly tool, called HiPerMAb that allows to evaluate pilot studies based on performance measures like multiclass AUC, entropy, area above the cost curve, hypervolume under manifold, and misclassification rate using Monte-Carlo simulations to compute the p-values and confidence intervals. The number of "good" biomarker candidates is compared to the expected number of "good" biomarker candidates in a data set with no association to the considered disease states. This allows judging the potential in the pilot study even if statistical tests with correction for multiple testing fail to provide any hint of significance.

Interplay between Porphyromonas gingivalis Hemophore-Like Protein HmuY and Kgp/RgpA Gingipains Plays a Superior Role in Heme Supply

To acquire heme as a source of iron and protoporphyrin IX, Porphyromonas gingivalis uses gingipains, Hmu, and Hus systems. The aim of this study was to assess the correlation between the production and function of the most important virulence factors of P. gingivalis involved in heme supply, namely, hemophore-like proteins (HmuY and HusA) and gingipains. Respective mutant strains were used, and the expression of genes at the transcript and protein levels, as well as the importance of these genes' products for virulence potential, was examined. We found that HmuY and Kgp/RgpA gingipains are among the main P. gingivalis virulence factors synergistically engaged in heme supply. Their expression is related mainly when P. gingivalis grows in conditions rich in iron and heme sources, resembling those found in severe periodontitis. We confirmed that HmuY production is strictly dependent on the availability of heme and iron in the external environment, whereas we did not observe such dependence in the production of HusA. Moreover, we found that the HmuY protein can easily sequester heme from the HusA protein. The only correlation in the production of HmuY and HusA hemophore-like proteins could occur in P. gingivalis grown in conditions rich in iron and heme sources, mimicking an environment typical for severe periodontitis. Based on our observations, we suggest that HmuY is the major heme-binding protein produced by P. gingivalis, especially in iron- and heme-depleted conditions, typical for healthy periodontium and the initial stages of infection. The HusA protein could play a supporting role in P. gingivalis heme uptake. IMPORTANCE Altered or disturbed mutualism between oral microbiome members results in dysbiosis with local injuries and subsequently in systemic diseases. Periodontitis belongs to a group of multifactorial infectious diseases, characterized by inflammation and destruction of tooth-supporting tissues. Porphyromonas gingivalis is considered the main etiologic agent and keystone pathogen responsible for developing advanced periodontitis. As part of the infective process, P. gingivalis must acquire heme to survive and multiply at the infection site. Analysis of the mutual relationship between its main virulence factors showed that heme acquisition in P. gingivalis is a complex process in which mainly the Hmu system, with the leading role played by the HmuY hemophore-like protein, and Kgp and RgpA gingipains prefer cooperative interplay. It seems that the Hus system, including HusA hemophore-like protein, could be involved in another, so far uncharacterized, stage of iron and heme supply.

Oral Microorganisms and Biofilms: New Insights to Defeat the Main Etiologic Factor of Oral Diseases

The oral cavity presents a highly diverse community of microorganisms due to the unique environmental conditions for microbial adhesion and growth [...].

Oral biofilm dysbiosis during experimental periodontitis

OBJECTIVES

We have previously characterized the main osteoimmunological events that occur during ligature periodontitis. This study aims to determine the polymicrobial community shifts that occur during disease development.

METHODS

Periodontitis was induced in C57BL/6 mice using the ligature-induced periodontitis model. Healthy oral mucosa swabs and ligatures were collected every 3 days from 0 to 18 days post-ligature placement. Biofilm samples were evaluated by 16SrRNA gene sequencing (Illumina MiSeq) and QIIME. Time-course changes were determined by relative abundance, diversity, and rank analyses (PERMANOVA, Bonferroni-adjusted).

RESULTS

Microbial differences between health and periodontal inflammation were observed at all phylogenic levels. An evident microbial community shift occurred in 25 genera during the advancement of "gingivitis" (3-6 days) to periodontitis (9-18 days). From day 0 to 18, dramatic changes were identified in Streptococcus levels, with an overall decrease (54.04%-0.02%) as well an overall increase of Enterococcus and Lactobacillus (23.7%-73.1% and 10.1%-70.2%, respectively). Alpha-diversity decreased to its lowest at 3 days, followed by an increase in diversity as disease advancement. Beta-diversity increased after ligature placement, indicating that bone loss develops in response to a greater microbial variability (p = 0.001). Levels of facultative and strict anaerobic bacteria augmented over the course of disease progression, with a total of eight species significantly different during the 18-day period.

CONCLUSION

The data supports that murine gingival inflammation and alveolar bone loss develop in response to microbiome shifts. Bacterial diversity increased during progression to bone loss. These findings further support the utilization of the periodontitis ligature model for microbial shift analysis under different experimental conditions.

Differences in the subgingival microbiome according to stage of periodontitis: A comparison of two geographic regions

No microbiological criteria were included in the 2018 EFP-AAP classification of periodontal diseases that could be used to differentiate between stages and grades. Furthermore, differences in the subgingival microbiome depending on stage and grade have not been established. Sixty subgingival biofilm samples were collected in Spain (n = 30) and Colombia (n = 30) from three distinct patient categories: those with periodontal health/gingivitis (n = 20), those with stage I-II periodontitis (n = 20), and those with stage III-IV periodontitis (n = 20). Patients were evaluated by 16S rRNA gene amplification sequencing. Amplicon sequence variants were used to assign taxonomic categories compared to the Human Oral Microbiome Database (threshold ≥97% identity). Alpha diversity was established by Shannon and Simpson indices, and principal coordinate analysis, ANOSIM, and PERMANOVA of the UNIFRAC distances were performed using QIIME2. Although differences in the alpha diversity were observed between samples according to country, Filifactor alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Fretibacterium fastidiosum, Lachnospiraceae [G-8] bacterium HMT 500, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, Peptostreptococcus stomatis, and Tannerella forsythia were associated with periodontitis sites in all stages. However, only F. alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Peptostreptococcaceae [XI][G-9] [Eubacterium] brachy, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, and Desulfobulbus sp. HMT 041 were consistent in stage III-IV periodontitis in both countries. Porphyromonas gingivalis and Tannerella forsythia were differentially expressed in severe lesions in the countries studied. Although some non-cultivable microorganisms showed differential patterns between the different stages of periodontitis, they were not the same in the two countries evaluated. Further studies using larger samples with advanced next-generation techniques for high-throughput sequencing of phyla and non-cultivable bacteria within the subgingival microbiome could provide more insight into the differences between stages of periodontitis.

Pharmacokinetic profile and effect on the faecal microbiome of a single dose of pradofloxacin oral suspension in the rabbit (Oryctolagus cuniculus)

Fluoroquinolones are often administered to pet rabbits given their perceived safety and limited effects on anaerobic gut microbiota. However, the pharmacokinetics and relative safety of pradofloxacin, a third-generation veterinary fluoroquinolone with a much broader spectrum of activity, have not been reported in this species. Here, we determined the pharmacokinetic profile of a single dose of oral pradofloxacin in rabbits and evaluated effects on the faecal microbiome. Four mature female rabbits were administered pradofloxacin (25 mg/ml oral suspension), at a dose of 7.5 mg/kg. The pradofloxacin median (range) T_max was 4.50 (2.00-5.00) h, C_max 600.66 (395.85-886.72) ng/ml and t_½ was 1.27 (0.12-1.39) h. These results indicated that oral absorption of pradofloxacin was slower, and elimination faster compared with other fluoroquinolones in healthy rabbits, as well as relative to cats and dogs. Following treatment with pradofloxacin, faecal microbiota profiling showed some compositional differences between treated and control animals. This was the result of a significant decrease in the abundance of Proteobacteria, in particular bacteria belonging to the Pseudomonas, Atopostipes and Parabacteroides genera. The pharmacokinetic profile of pradofloxacin in rabbits should be further studied by increasing the sample size and using multiple-dose protocols (i.e. 7 days) to confirm safety. Further information on the effects of protein binding, higher dosages and disease on pradofloxacin pharmacokinetics in rabbits are needed before an accurate dosing regimen can be recommended.

Porphyromonas spp., Fusobacterium spp., and Bacteroides spp. dominate microbiota in the course of macropod progressive periodontal disease

Macropod progressive periodontal disease (MPPD) is a necrotizing, polymicrobial, inflammatory disease commonly diagnosed in captive macropods. MPPD is characterized by gingivitis associated with dental plaque formation, which progresses to periodontitis and then to osteomyelitis of the mandible or maxilla. However, the underlying microbial causes of this disease remain poorly understood. In this study, we collected 27 oral plaque samples and associated clinical records from 22 captive Macropodidae and Potoroidae individuals that were undergoing clinical examination at Adelaide and Monarto Zoos in South Australia (15 healthy, 7 gingivitis and 5 periodontitis-osteomyelitis samples). The V3-V4 region of the 16S ribosomal RNA gene was sequenced using an Illumina Miseq to explore links between MPPD and oral bacteria in these animals. Compositional differences were detected between the microbiota of periodontitis-osteomyelitis cases compared to healthy samples (p-value with Bonferroni correction < 0.01), as well as gingivitis cases compared to healthy samples (p-value with Bonferroni correction < 0.05) using Permutational Multivariate Analysis of Variance (PERMANOVA). An overabundance of Porphyromonas, Fusobacterium, and Bacteroides taxa was also identified in animals with MPPD compared to healthy individuals using linear discriminant analysis effect size (LEfSe; p =  < 0.05). An increased abundance of Desulfomicrobium also was detected in MPPD samples (LEfSe; p < 0.05), which could potentially reflect differences in disease progression. This is the first microbiota analysis of MPPD in captive macropods, and these results support a polymicrobial pathogenesis of MPPD, suggesting that the microbial interactions underpinning MPPD may be more complex than previously documented.

Tracking the transition to agriculture in Southern Europe through ancient DNA analysis of dental calculus

Archaeological dental calculus, or mineralized plaque, is a key tool to track the evolution of oral microbiota across time in response to processes that impacted our culture and biology, such as the rise of farming during the Neolithic. However, the extent to which the human oral flora changed from prehistory until present has remained elusive due to the scarcity of data on the microbiomes of prehistoric humans. Here, we present our reconstruction of oral microbiomes via shotgun metagenomics of dental calculus in 44 ancient foragers and farmers from two regions playing a pivotal role in the spread of farming across Europe-the Balkans and the Italian Peninsula. We show that the introduction of farming in Southern Europe did not alter significantly the oral microbiomes of local forager groups, and it was in particular associated with a higher abundance of the species Olsenella sp. oral taxon 807. The human oral environment in prehistory was dominated by a microbial species, Anaerolineaceae bacterium oral taxon 439, that diversified geographically. A Near Eastern lineage of this bacterial commensal dispersed with Neolithic farmers and replaced the variant present in the local foragers. Our findings also illustrate that major taxonomic shifts in human oral microbiome composition occurred after the Neolithic and that the functional profile of modern humans evolved in recent times to develop peculiar mechanisms of antibiotic resistance that were previously absent.

Subgingival Microbiome and Specialized Pro-Resolving Lipid Mediator Pathway Profiles Are Correlated in Periodontal Inflammation

Failure of resolution pathways in periodontitis is reflected in levels of specialized pro-resolving lipid mediators (SPMs) and SPM pathway markers but their relationship with the subgingival microbiome is unclear. This study aimed to analyze and integrate lipid mediator level, SPM receptor gene expression and subgingival microbiome data in subjects with periodontitis vs. healthy controls. The study included 13 periodontally healthy and 15 periodontitis subjects that were evaluated prior to or after non-surgical periodontal therapy. Samples of gingival tissue and subgingival plaque were collected prior to and 8 weeks after non-surgical treatment; only once in the healthy group. Metabololipidomic analysis was performed to measure levels of SPMs and other relevant lipid mediators in gingiva. qRT-PCR assessed relative gene expression (2-ΔΔCT) of known SPM receptors. 16S rRNA sequencing evaluated the relative abundance of bacterial species in subgingival plaque. Correlations between lipid mediator levels, receptor gene expression and bacterial abundance were analyzed using the Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) and Sparse Partial Least Squares (SPLS) methods. Profiles of lipid mediators, receptor genes and the subgingival microbiome were distinct in the three groups. The strongest correlation existed between lipid mediator profile and subgingival microbiome profile. Multiple lipid mediators and bacterial species were highly correlated (correlation coefficient ≥0.6) in different periodontal conditions. Comparing individual correlated lipid mediators and bacterial species in periodontitis before treatment to healthy controls revealed that one bacterial species, Corynebacterium durum, and five lipid mediators, 5(S)6(R)-DiHETE, 15(S)-HEPE, 7-HDHA, 13-HDHA and 14-HDHA, were identified in both conditions. Comparing individual correlated lipid mediators and bacterial species in periodontitis before treatment to after treatment revealed that one bacterial species, Anaeroglobus geminatus, and four lipid mediators, 5(S)12(S)-DiHETE, RvD1, Maresin 1 and LTB4, were identified in both conditions. Four Selenomonas species were highly correlated with RvD1, RvE3, 5(S)12(S)-DiHETE and proinflammatory mediators in the periodontitis after treatment group. Profiles of lipid mediators, receptor gene and subgingival microbiome are associated with periodontal inflammation and correlated with each other, suggesting inflammation mediated by lipid mediators influences microbial composition in periodontitis. The role of correlated individual lipid mediators and bacterial species in periodontal inflammation have to be further studied.

Short-term improvement of clinical parameters and microbial diversity in periodontitis patients following Indocyanine green-based antimicrobial photodynamic therapy: A randomized single-blind split-mouth cohort

BACKGROUND

Indocyanine green-mediated photodynamic therapy is effective against chronic periodontitis. Here, we evaluated the efficiency of indocyanine green-based adjunctive antimicrobial photodynamic therapy in non-surgical treatment of chronic periodontitis patients.

METHODS

Fifty-six periodontally involved teeth of 20 patients were treated with "scaling and root planing" (control group) or "scaling and root planing with indocyanine green-based (perio-green, 0.1 mg/ml) antimicrobial photodynamic therapy" (test group) using a split-mouth design. We performed clinical assessment of probing depth, gingival recession, clinical attachment loss, and other indices, while plaque samples were collected for microbiome analysis.

RESULTS

At baseline, periodontal depth and clinical attachment loss were significantly higher in the test group (p < 0.05), and at 1-month post-treatment, we observed a significant favorable reduction of both periodontal depth and clinical attachment loss in test and control sites, with lower means maintained at 3 months (p = 0.01 and p = 0.000, respectively). Additionally, analysis of variance showed significant improvements in periodontal depth and clinical attachment loss in the indocyanine green-antimicrobial photodynamic therapy group (p = 0.001), although not for clinical attachment loss in controls (p = 0.102). Moreover, a significant reduction was observed in test sites for bleeding on probing and residual pocket post-therapy (p = 0.04 and p = 0.0001 respectively). Furthermore, microbiome analysis identified Porphyromonons gingivalis, Treponema, and Tannerella in all samples with favorable changes in test sites (p = 0.07).

CONCLUSION

We observed a significant reduction in periodontal clinical parameters (periodontal depth and clinical attachment loss) in chronic periodontitis patients treated with antimicrobial photodynamic therapy as an adjunctive procedure to conventional scaling and root planing. This improvement was associated with periodontal pathogen reduction and increase in the healthy subgingival microbiome.

Removable denture is a risk indicator for peri-implantitis and facilitates expansion of specific periodontopathogens: a cross-sectional study

Background

The prevalence of peri-implantitis ranges between 7 and 38.4% depending on risk indicators such as smoking, diabetes mellitus, lack of periodontal maintenance program, and history or presence of periodontitis. Currently, the possible effect of the type of superstructure on peri-implant health is unclear. This cross-sectional study aims to investigate the influence of the superstructure on the prevalence of peri-implant mucositis, peri-implantitis and peri-implant dysbiosis.

Methods

During a 32-month recruitment period dental implants were assessed to diagnose healthy peri-implant tissues, mucositis or peri-implantitis. The study included 1097 implants in 196 patients. Out of all peri-implantitis cases 20 randomly chosen submucosal biofilms from implants with fixed denture (FD) originating from 13 patients and 11 biofilms from implants with removable dentures (RD) originating from 3 patients were studied for microbiome analysis. Composition of transcriptionally active biofilms was revealed by RNAseq. Metatranscriptomic profiles were created for thirty-one peri-implant biofilms suffering from peri-implantitis and microbiome changes associated with superstructure types were identified.

Results

16.41% of the implants were diagnosed with peri-implantitis, 25.00% of implants with RD and 12.68% of implants with FD, respectively. Multivariate analysis showed a significant positive association on patient (p =  < 0.001) and implant level (p = 0.03) between the prevalence of peri-implantitis and RD. Eight bacterial species were associated either with FD or RD by linear discriminant analysis effect size method. However, significant intergroup confounders (e.g. smoking) were present.

Conclusions

Within the limitations of the present work, RDs appear to be a risk indicator for peri-implantitis and seem to facilitate expansion of specific periodontopathogens. Potential ecological and pathological consequences of shift in microbiome from RDs towards higher activity of Fusobacterium nucleatum subspecies animalis and Prevotella intermedia require further investigation.

The Oral Microbiome in Periodontal Health

The estimation of oral microbiome (OM) taxonomic composition in periodontally healthy individuals can often be biased because the clinically periodontally healthy subjects for evaluation can already experience dysbiosis. Usually, they are included just based on the absence of clinical signs of periodontitis. Additionally, the age of subjects is used to be higher to correspond well with tested groups of patients with chronic periodontitis, a disorder typically associated with aging. However, the dysbiosis of the OM precedes the clinical signs of the disease by many months or even years. The absence of periodontal pockets thus does not necessarily mean also good periodontal health and the obtained image of "healthy OM" can be distorted.To overcome this bias, we taxonomically characterized the OM in almost a hundred young students of dentistry with precise oral hygiene and no signs of periodontal disease. We compared the results with the OM composition of older periodontally healthy individuals and also a group of patients with severe periodontitis (aggressive periodontitis according to former classification system). The clustering analysis revealed not only two compact clearly separated clusters corresponding to each state of health, but also a group of samples forming an overlap between both well-pronounced states. Additionally, in the cluster of periodontally healthy samples, few outliers with atypical OM and two major stomatotypes could be distinguished, differing in the prevalence and relative abundance of two main bacterial genera: Streptococcus and Veillonella. We hypothesize that the two stomatotypes could represent the microbial succession from periodontal health to starting dysbiosis. The old and young periodontally healthy subjects do not cluster separately but a trend of the OM in older subjects to periodontitis is visible. Several bacterial genera were identified to be typically more abundant in older periodontally healthy subjects.

The human oral phageome

Oral bacteriophages (or phages), especially periodontal ones, constitute a growing area of interest, but research on oral phages is still in its infancy. Phages are bacterial viruses that may persist as intracellular parasitic deoxyribonucleic acid (DNA) or use bacterial metabolism to replicate and cause bacterial lysis. The microbiomes of saliva, oral mucosa, and dental plaque contain active phage virions, bacterial lysogens (ie, carrying dormant prophages), and bacterial strains containing short fragments of phage DNA. In excess of 2000 oral phages have been confirmed or predicted to infect species of the phyla Actinobacteria (>300 phages), Bacteroidetes (>300 phages), Firmicutes (>1000 phages), Fusobacteria (>200 phages), and Proteobacteria (>700 phages) and three additional phyla (few phages only). This article assesses the current knowledge of the diversity of the oral phage population and the mechanisms by which phages may impact the ecology of oral biofilms. The potential use of phage-based therapy to control major periodontal pathogens is also discussed.

R/G Value-A Numeric Index of Individual Periodontal Health and Oral Microbiome Dynamics

The dysbiosis of oral microbiome (OM) precedes the clinical signs of periodontal disease. Its simple measure thus could indicate individuals at risk of periodontitis development; however, such a tool is still missing. Up to now, numerous microbial taxa were associated with periodontal health or periodontitis. The outputs of most studies could, nevertheless, be slightly biased from following two reasons: First, the healthy group is often characterized only by the absence of the disease, but the individuals could already suffer from dysbiosis without any visible signs. Second, the healthy/diseased OM characteristics are frequently determined based on average data obtained for whole groups of periodontally healthy persons versus patients. Especially in smaller sets of tested individuals the typical individual variability can thus complicate the unambiguous assignment of oral taxa to respective state of health. In this work the taxonomic composition of OM was evaluated for 20 periodontally healthy individuals and 15 patients with chronic periodontitis. The narrowed selection set of the most diseased patients (confirmed by clinical parameters) and the most distant group of healthy individuals with the lowest probability of dysbiosis was determined by clustering analysis and used for identification of marker taxa. Based on their representation in each individual oral cavity we proposed the numeric index of periodontal health called R/G value. Its diagnostic potential was further confirmed using independent set of 20 periodontally healthy individuals and 20 patients with periodontitis with 95 percent of samples assigned correctly. We also assessed the individual temporal OM dynamics in periodontal health and we compared it to periodontitis. We revealed that the taxonomic composition of the system changes dynamically but generally it ranges within values typical for periodontal health or transient state, but far from values typical for periodontitis. R/G value tool, formulated from individually evaluated data, allowed us to arrange individual OMs into a continuous series, instead of two distinct groups, thus mimicking the gradual transformation of a virtual person from periodontal health to disease. The application of R/G value index thus represents a very promising diagnostic tool for early prediction of persons at risk of developing periodontal disease.

Bacterial community structure in acidic gruel from different regions and its influence on quality

Acidic gruel is a popular and nutritious fermented cereal food in China. However, the relationship between microbial function and quality of traditionally-fermented acidic gruel has not been evaluated. In this study, the microbiome, sensory quality and nutritional components of 98 samples of naturally fermented acidic gruel collected from Guangxi, Shanxi and Inner Mongolia were analyzed by high-throughput sequencing combined with various determination methods. High-throughput sequencing showed bacteria in acidic gruel belonged mainly to the genera Lactobacillus, Acetobacter, Bacillus, Clostridium and Weissella. Bacterial community composition and sensory quality of samples from Shanxi and Inner Mongolia were similar, but significantly different from Guangxi samples (p < 0.05). PICRUSt showed that gene functions were mostly related to carbohydrate and amino acid metabolism; all dominant bacterial genera, except Lactobacillus, were related to taste and volatile flavour indices. Acidic gruel was rich in amino acids, organic acids and soluble solids, which were in significantly higher concentrations in samples from Guangxi than in samples from Shanxi and Inner Mongolia; pH values of samples from Guangxi were also the highest. These differences may be caused by geographical, environmental or manufacturing differences.

Effect of DLT-SML on Chronic Stable Angina Through Ameliorating Inflammation, Correcting Dyslipidemia, and Regulating Gut Microbiota

ABSTRACT

Chronic stable angina (CSA) is caused by coronary atherosclerosis. The gut microbiota (GM) and their metabolite trimethylamine-N-oxide (TMAO) levels are associated with atherosclerosis. Danlou tablet (DLT) combined with Salvia miltiorrhiza ligustrazine (SML) injection has been used to treat CSA. This study aims to investigate how DLT combined with SML (DLT-SML) regulates serum lipids, inflammatory cytokines, GM community, and microbial metabolite in patients with CSA. In this study, 30 patients with CSA were enrolled in the DLT-SML group, and 10 healthy volunteers were included in the healthy control group. The patients in the DLT-SML group were subdivided as the normal total cholesterol (TC) group and high-TC group according to their serum TC level before treatment. Blood samples were collected to investigate the (1) lipid content, including triglyceride (TG), TC, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol, (2) fasting blood glucose (Glu), (3) inflammatory cytokines, including interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α), and (4) gut-derived metabolite, including lipopolysaccharides and TMAO level. GM composition was analyzed by sequencing 16S rRNA of fecal samples. Results showed that DLT-SML significantly decreased serum TG, TC, low-density lipoprotein cholesterol, IL-1β, TNF-α, and TMAO levels of patients with CSA. DLT-SML increased the abundance of Firmicutes and decreased Proteobacteria, which were significantly lower or higher in patients with CSA, respectively, compared with the healthy control group. In particular, DLT-SML increased the microbial diversity and decreased Firmicutes/Bacteroidetes ratio of patients with high-TC. The abundance of Sarcina, Anaerostipes, Streptococcus, Weissella, and Erysipelatoclostridium was decreased, whereas Romboutsia, Faecalibacterium, and Subdoligranulum were increased by DLT-SML treatment in patients with CSA. These findings indicated that DLT-SML improved patients with CSA by ameliorating dyslipidemia profile, decreasing the circulating inflammatory cytokines, and regulating the GM composition and their metabolites.

Metagenomic Sequencing Revealed the Potential Pathogenic Threats of Banknotes

Banknotes have long been suspected to be biologically "dirty" due to their frequent human contact, which may transmit human microbial pathogens. Still, it is an unsettled issue whether the microbes on banknotes pose a real threat to human health. In several previous studies, metagenomic sequencing was used to reveal the diversities of microbes on banknotes but live microorganism culture and functional verification were lacking. In this study, we collected banknotes of RMB in China as well as dollar bills in the United States and analyzed the microbial biodiversity and drug resistance genes carried by the identified microbes by metagenomic sequencing and in vitro culture methods. We identified eight major genera of drug-resistant bacteria through screening of 30 antibiotics, and the blood agar plate culture uncovered six pathogenic fungal species. Numerous phage and six dangerous viral sequences were also found. These results should substantiate our concern about the potential risk of banknotes to human health.

Dysbiosis of urine microbiota in obstructive urinary retention patients revealed by next-generation sequencing

BACKGROUND

Urinary retention (UR) is a common urinary system disease can be caused by urinary tract obstruction with numerous reasons, however, the role of urine microbes in these disorders is still poorly understood. The aim of this study was to identify the urine microbial features of two common types of obstructive UR, caused by urinary stones or urinary tract tumors, with comparison to healthy controls.

METHODS

Urine samples were collected from a cohort of 32 individuals with stone UR, 25 subjects with tumor UR and 25 healthy controls. The urine microbiome of all samples was analyzed using high-throughput 16S rRNA (16S ribosomal RNA) gene sequencing.

RESULTS

We observed dramatically increased urine microbial richness and diversity in both obstructive UR groups compared to healthy controls. Despite different origins of UR, bacteria such as Pseudomonas, Acinetobacter and Sphingomonas were enriched, while Lactobacillus, Streptococcus, Gardnerella, Prevotella and Atopobium were decreased in both UR groups in comparison with healthy controls, exhibited an approximate urine microbial community and functional characteristics of two types of obstructive UR. Furthermore, disease classifiers were constructed using specific enriched genera in UR, which can distinguish stone UR or tumor UR patients from healthy controls with an accuracy of 92.29% and 97.96%, respectively.

CONCLUSION

We presented comprehensive microbial landscapes of two common types of obstructive urinary retention and demonstrated that urine microbial features of these patients are significantly different from that of healthy people. The urine microbial signatures would shed light on the pathogenesis of these types of urinary retention and might be used as potential classification tools in the future.

Prediction of Chronic Periodontitis Severity Using Machine Learning Models Based On Salivary Bacterial Copy Number

Periodontitis is a widespread chronic inflammatory disease caused by interactions between periodontal bacteria and homeostasis in the host. We aimed to investigate the performance and reliability of machine learning models in predicting the severity of chronic periodontitis. Mouthwash samples from 692 subjects (144 healthy controls and 548 generalized chronic periodontitis patients) were collected, the genomic DNA was isolated, and the copy numbers of nine pathogens were measured using multiplex qPCR. The nine pathogens are as follows: Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), Prevotella intermedia (Pi), Fusobacterium nucleatum (Fn), Campylobacter rectus (Cr), Aggregatibacter actinomycetemcomitans (Aa), Peptostreptococcus anaerobius (Pa), and Eikenella corrodens (Ec). By adding the species one by one in order of high accuracy to find the optimal combination of input features, we developed an algorithm that predicts the severity of periodontitis using four machine learning techniques. The accuracy was the highest when the models classified “healthy” and “moderate or severe” periodontitis (H vs. M-S, average accuracy of four models: 0.93, AUC = 0.96, sensitivity of 0.96, specificity of 0.81, and diagnostic odds ratio = 112.75). One or two red complex pathogens were used in three models to distinguish slight chronic periodontitis patients from healthy controls (average accuracy of 0.78, AUC = 0.82, sensitivity of 0.71, and specificity of 0.84, diagnostic odds ratio = 12.85). Although the overall accuracy was slightly reduced, the models showed reliability in predicting the severity of chronic periodontitis from 45 newly obtained samples. Our results suggest that a well-designed combination of salivary bacteria can be used as a biomarker for classifying between a periodontally healthy group and a chronic periodontitis group.

Omics and interspecies interaction

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

Did Omics change periodontal therapy?

The starting point for defining effective treatment protocols is a clear understanding of the etiology and pathogenesis of a condition. In periodontal diseases, this understanding has been hindered by a number of factors, such as the difficulty in differentiating primary pathogens from nonpathogens in complex biofilm structures. The introduction of DNA sequencing technologies, including taxonomic and functional analyses, has allowed the oral microbiome to be investigated in much greater breadth and depth. This article aims to compile the results of studies, using next-generation sequencing techniques to evaluate the periodontal microbiome, in an attempt to determine how far the knowledge provided by these studies has brought us in terms of influencing the way we treat periodontitis. The taxonomic data provided, to date, by published association and elimination studies using next-generation sequencing confirm previous knowledge on the role of classic periodontal pathogens in the pathobiology of disease and include new species/genera. Conversely, species and genera already considered as host-compatible and others less explored were associated with periodontal health as their levels were elevated in healthy individuals and increased after therapy. Functional and transcriptomic analyses also demonstrated that periodontal biofilms are taxonomically diverse, functionally congruent, and highly cooperative. Very few interventional studies to date have examined the effects of treatment on the periodontal microbiome, and such studies are heterogeneous in terms of design, sample size, sampling method, treatment provided, and duration of follow-up. Hence, it is still difficult to draw meaningful conclusions from them. Thus, although OMICS knowledge has not yet changed the way we treat patients in daily practice, the information provided by these studies opens new avenues for future research in this field. As new pathogens and beneficial species become identified, future randomized clinical trials could monitor these species/genera more comprehensively. In addition, the metatranscriptomic data, although still embryonic, suggest that the interplay between the host and the oral microbiome may be our best opportunity to implement personalized periodontal treatments. Therapeutic schemes targeting particular bacterial protein products in subjects with specific genetic profiles, for example, may be the futuristic view of enhanced periodontal therapy.

Metatranscriptomic analyses of the oral microbiome

Although the composition of the oral human microbiome is now well studied, regulation of genes within oral microbial communities remains mostly uncharacterized. Current concepts of periodontal disease and caries highlight the importance of oral biofilms and their role as etiological agents of those diseases. Currently, there is increased interest in exploring and characterizing changes in the composition and gene-expression profiles of oral microbial communities. These efforts aim to identify changes in functional activities that could explain the transition from health to disease and the reason for the chronicity of those infections. It is now clear that the functions of distinct species within the subgingival microbiota are intimately intertwined with the rest of the microbial community. This point highlights the relevance of examining the expression profile of specific species within the subgingival microbiota in the case of periodontal disease or caries lesions, in the context of the other members of the biofilm in vivo. Metatranscriptomic analysis of the oral community is the starting point for identifying environmental signals that modulate the shift in metabolism of the community from commensal to dysbiotic. These studies give a snapshot of the expression patterns of microbial communities and also allow us to determine triggers to diseases. For example, in the case of caries, studies have unveiled a potential new pathway of sugar metabolism, namely the use of sorbitol as an additional source of carbon by Streptococcus mutans; and in the case of periodontal disease, high levels of extracellular potassium could be a signal of disease. Longitudinal studies are needed to identify the real markers of the initial stages of caries and periodontal disease. More information on the gene-expression profiles of the host, along with the patterns from the microbiome, will lead to a clearer understanding of the modulation of health and disease. This review presents a summary of these initial studies, which have opened the door to a new understanding of the dynamics of the oral community during the dysbiotic process in the oral cavity.

Impact of Local Drug Delivery of Minocycline on the Subgingival Microbiota during Supportive Periodontal Therapy: A Randomized Controlled Pilot Study

The aim of this study was to examine the effect of adjunct local minocycline administration on the microbiological parameters of subgingival plaque samples in the residual periodontal pockets. Ten chronic periodontitis patients under a supportive periodontal therapy regimen were recruited. After subgingival debridement, either 2% minocycline gel, Periocline™, (Test Group) or a placebo (Control Group) was administered to the selected sites once a week for three weeks. Subgingival plaque was collected at baseline, and at four weeks and eight weeks. The microbiological composition was analyzed by 16S ribosomal RNA sequencing. In the Test Group, α-diversity (evenness) decreased compared to the baseline (p = 0.005) and was lower compared to the control group at four weeks (p = 0.003). The microbial community composition between the two groups was significantly different at four weeks (p = 0.029). These changes were attributable to a decrease in the bacteria associated with periodontitis and an increase in the bacteria associated with periodontal health. Additionally, the improvement in bleeding on probing continued at eight weeks; however, there were little microbial effects of 2% minocycline gel observed at eight weeks. The control group demonstrated no change throughout the eight-week experimental period. Thus, local minocycline administration can change the subgingival microbial community of residual periodontal pockets.

Temporal transcriptional patterns of cyanophage genes suggest synchronized infection of cyanobacteria in the oceans

BACKGROUND

Based on the peak expression times during infection, early, middle, and late genes have been characterized in viruses (cyanophages) that infect the unicellular cyanobacterium Prochlorococcus. Laboratory experiments show that some cyanophages can only replicate in the light and thus exhibit diurnal infection rhythms under light-dark cycles. Field evidence also suggests synchronized infection of Prochlorococcus by cyanophages in the oceans, which should result in progressive expression of cyanophage early, middle, and late genes. However, distinct temporal expression patterns have not been observed in cyanophage field populations.

RESULTS

In this study, we reanalyzed a previous metatranscriptomic dataset collected in the North Pacific Subtropical Gyre. In this dataset, it was previously shown that aggregate transcripts from cyanophage scaffolds display diurnal transcriptional rhythms with transcript abundances decreasing at night. By mapping metatranscriptomic reads to individual viral genes, we identified periodically expressed genes from putative viruses infecting the cyanobacteria Prochlorococcus and Synechococcus, heterotrophic bacteria, and algae. Of the 41 cyanophage genes, 35 were from cyanomyoviruses. We grouped the periodically expressed cyanomyovirus genes into early, middle, and late genes based on the conserved temporal expression patterns of their orthologs in cyanomyovirus laboratory cultures. We found that the peak expression times of late genes in cyanophage field populations were significantly later than those of early and middle genes, which were similar to the temporal expression patterns of synchronized cyanophage laboratory cultures.

CONCLUSIONS

The significantly later peak expression times of late genes in cyanomyovirus field populations suggest that cyanophage infection of Prochlorococcus is synchronized in the North Pacific Subtropical Gyre. The night-time peak expression of late genes also suggests synchronized lysis of Prochlorococcus at night, which might result in synchronized release of dissolved organic matter to the marine food web. Video abstract.

Comparison of the Microbiota and Inorganic Anion Content in the Saliva of Patients with Gastroesophageal Reflux Disease and Gastroesophageal Reflux Disease-Free Individuals

The oral cavity is one of the most complex microbial environments; however, the complex nature of the salivary microbiota and the level of inorganic anions in the saliva of subjects with and without gastroesophageal reflux disease (GERD) are poorly understood. The primary goals of this pilot research were to assess differences in salivary bacterial community composition and inorganic anion concentrations between patients with GERD and GERD-free people. Thus, the salivary microbiota within both groups was dominated by these genera: Streptococcus, Prevotella, Porphyromonas, Veillonella, Neisseria, Haemophilus, Fusobacterium, Rothia, and Leptotrichia. However, the relative abundances of the genera Actinomyces, Atopobium, Stomatobaculum, Ruminococcaceae_[G-2], Veillonella, and Leptotrichia were significantly higher in the saliva samples of patients with GERD, while the genera Porphyromonas, Gemella, Peptostreptococcus, and Neisseria were less abundant in this group. The concentrations of chloride, phosphate, and sulphate ions in the human saliva varied among all subjects and sampling time. These results broaden our knowledge of the salivary microbial community composition and chemistry of saliva of patients with GERD and GERD-free individuals.

Deep DNA metagenomic sequencing reveals oral microbiome divergence between monozygotic twins discordant for multiple sclerosis severity

In contrast to gut, the oral microbiome of MS patients has not been characterized. Deep sequencing of saliva DNA from a pair of monozygotic twins (MSF1 with relapsing remitting MS; MSF2 with clinically isolated syndrome) identified 2036 bacterial species. Relative abundances of 3 phyla were higher, and 3 lower in MSF1 versus MSF2. Species diversity was greater in MSF2, and 20 abundant species differed at least 2-fold. Pathway analysis identified 116 functional hierarchies differing 50% or more. Although limited to one pair of twins, our data suggests that oral microbiome analysis may be useful for diagnosis or monitoring therapeutic efficacy.

FBA Ecological Guild: Trio of Firmicutes-Bacteroidetes Alliance against Actinobacteria in Human Oral Microbiome

In a pioneering study, Zaura et al. (2009) found that majority of oral microbes fall within the five phyla including, Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes and Fusobacteria. Subsequent studies further identified a set of microbes that were commonly shared among unrelated individuals (i.e., core). However, these existing studies may have not been designed to investigate the interactions among various core species. Here by harnessing the power of ecological network analysis, we identified some important ecological guilds in the form of network clusters. In particular, we found that the strongest cluster is an alliance between Firmicutes and Bacteroidetes against Actinobacteria (FBA-guild). Within the guild, we further identified two sub-guilds, the Actinobacteria-dominant sub-guild (ASG) and Firmicutes-dominant allied with Bacteroidetes sub-guild (FBSG). Furthermore, we identified so-termed guard nodes in both sub-guilds, and their role may be to inhibit the peer sub-guild given they held competitive interactions only with the outside nodes only but held cooperative interactions only with the internal nodes, which we termed civilian nodes given that they only held cooperative interactions. We postulated that FBA-guild might be to do with protection of oral health against some opportunistic pathogens from Corynebacterium and Actinomyces, the two major genera of Actinobacteria (target of FB alliance).

Commensal and pathogenic biofilms differently modulate peri-implant oral mucosa in an organotypic model

The impact of oral commensal and pathogenic bacteria on peri-implant mucosa is not well understood, despite the high prevalence of peri-implant infections. Hence, we investigated responses of the peri-implant mucosa to Streptococcus oralis or Aggregatibacter actinomycetemcomitans biofilms using a novel in vitro peri-implant mucosa-biofilm model. Our 3D model combined three components, organotypic oral mucosa, implant material, and oral biofilm, with structural assembly close to native situation. S. oralis induced a protective stress response in the peri-implant mucosa through upregulation of heat shock protein (HSP70) genes. Attenuated inflammatory response was indicated by reduced cytokine levels of interleukin-6 (IL-6), interleukin-8 (CXCL8), and monocyte chemoattractant protein-1 (CCL2). The inflammatory balance was preserved through increased levels of tumor necrosis factor-alpha (TNF-α). A. actinomycetemcomitans induced downregulation of genes important for cell survival and host inflammatory response. The reduced cytokine levels of chemokine ligand 1 (CXCL1), CXCL8, and CCL2 also indicated a diminished inflammatory response. The induced immune balance by S. oralis may support oral health, whereas the reduced inflammatory response to A. actinomycetemcomitans may provide colonisation advantage and facilitate later tissue invasion. The comprehensive characterisation of peri-implant mucosa-biofilm interactions using our 3D model can provide new knowledge to improve strategies for prevention and therapy of peri-implant disease.

Microbiota fingerprints within the oral cavity of cetaceans as indicators for population biomonitoring

The composition of mammalian microbiota has been related with the host health status. In this study, we assessed the oral microbiome of 3 cetacean species most commonly found stranded in Iberian Atlantic waters (Delphinus delphis, Stenella coeruleoalba and Phocoena phocoena), using 16S rDNA-amplicon metabarcoding. All oral microbiomes were dominated by Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria bacteria, which were also predominant in the oral cavity of Tursiops truncatus. A Constrained Canonical Analysis (CCA) showed that the major factors shaping the composition of 38 oral microbiomes (p-value < 0.05) were: (i) animal species and (ii) age class, segregating adults and juveniles. The correlation analysis also grouped the microbiomes by animal stranding location and health status. Similar discriminatory patterns were detected using the data from a previous study on Tursiops truncatus, indicating that this correlation approach may facilitate data comparisons between different studies on several cetacean species. This study identified a total of 15 bacterial genera and 27 OTUs discriminating between the observed CCA groups, which can be further explored as microbiota fingerprints to develop (i) specific diagnostic assays for cetacean population conservation and (ii) bio-monitoring approaches to assess the health of marine ecosystems from the Iberian Atlantic basin, using cetaceans as bioindicators.

A Literature Review of Metagenomics and Culturomics of the Peri-implant Microbiome: Current Evidence and Future Perspectives

Background and objectives: In recent years, many different culture-independent molecular techniques have been developed with the aim of investigating the not yet cultivated part of the resident flora of the oral cavity and of analyzing the peri-implant and periodontal flora both in healthy and diseased sites. The most used technologies are Roche 454 pyrosequencing, Illumina HiSeq/MiSeq, ABI SOLiD and Ion Torrent. Due to these methods, two different approaches are available: Metagenomics and the 16S gene analysis. A complementary strategy was also recently developed: Culturomics. Culturomics consists of different culture conditions that allow a very rapid bacterial identification. The focused question of this review was developed in PICO format in order to investigate the role of metagenomics, 16S gene analysis and culturomics (interventions) in the differential study (comparison) of the peri-implant and periodontal microbiome (outcome) in humans (participants). The secondary aim was the characterization of currents limits and future applications of the three techniques. Methods: The authors performed a literature search on three databases (Web of Science, Scopus and PubMed) from 01/01/2003 to 31/06/2019. Date of last search was: 25/08/19. Any type of article dealing with the analysis of periodontal and peri-implant flora with metagenomic, culturomic or 16S gene analysis was included. No language restrictions were applied. Risk of bias for RCT was assessed using the Cochrane collaboration's tool whereas case-control and cohort studies were evaluated through the Newcastle-Ottawa scale. Results: The initial search resulted in 330 titles in total. After careful evaluation of all results no studies were found to satisfy the primary outcome of the present review. Hence a narrative review dealing with the secondary aim was performed. Conclusions: Metagenomic and 16S gene analysis approaches contributed in clarifying some crucial aspects of the oral microbiome. Based on the reported evidence some bacteria could be found around teeth and implants even in the absence of signs of inflammation and other species are more frequently found in supragingival peri-implant biofilm. Teeth and implants (even if adjacent) seem not to share the same microbiome and healthy teeth have a more diversified one. The same analyses also highlighted that the oral biofilm of smokers is composed by more periodontopathogen bacteria compared to non-smokers and that geographical location and ethnicity seem to play a role in bacterial composition. Culturomics, which has not yet been applied to the study of oral microbiota, consists of the use of different culture conditions and of the identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) with the aim of increasing the bacterial repertoire and avoiding the limits of molecular methods. In order to better evaluate perspectives and limits of the all presented approaches further studies comparing the different molecular techniques are encouraged. This review received no funding.

Japanese subgingival microbiota in health vs disease and their roles in predicted functions associated with periodontitis

The present study aimed to identify and compare the microbial signatures between periodontally healthy and periodontitis subjects using 454 sequences of 16S rRNA genes. Subgingival plaque samples were collected from ten periodontally healthy subjects and ten matched chronic periodontitis patients. Bacterial DNA was extracted and next-generation sequencing of 16S rRNA genes was performed. The microbial composition differed between healthy subjects and periodontitis patients at all phylogenetic levels. Particularly, 16 species, including Lautropia mirabilis and Neisseria subflava predominated in healthy subjects, whereas nine species, including Porphyromonas gingivalis and Filifactor alocis predominated in periodontitis. UniFrac, a principal coordinate and network analysis, confirmed distinct community profiles in healthy subjects and periodontitis patients. Using predicted function profiling, pathways involved in phenylpropanoid, GPI-anchor biosynthesis, and metabolism of alanine, arginine, aspartate, butanoate, cyanoamino acid, fatty acid, glutamate, methane, proline, and vitamin B6 were significantly over-represented in periodontitis patients. These results highlight the oral microbiota alterations in microbial composition in periodontitis and suggest the genes and metabolic pathways associated with health and periodontitis. Our findings help to further elucidate microbial composition and interactions in health and periodontitis.

Diversity patterns of bacteriophages infecting Aggregatibacter and Haemophilus species across clades and niches

Aggregatibacter and Haemophilus species are relevant human commensals and opportunistic pathogens. Consequently, their bacteriophages may have significant impact on human microbial ecology and pathologies. Our aim was to reveal the prevalence and diversity of bacteriophages infecting Aggregatibacter and Haemophilus species that colonize the human body. Genome mining with comparative genomics, screening of clinical isolates, and profiling of metagenomes allowed characterization of 346 phages grouped in 52 clusters and 18 superclusters. Less than 10% of the identified phage clusters were represented by previously characterized phages. Prophage diversity patterns varied significantly for different phage types, host clades, and environmental niches. A more diverse phage community lysogenizes Haemophilus influenzae and Haemophilus parainfluenzae strains than Aggregatibacter actinomycetemcomitans and “Haemophilus ducreyi”. Co-infections occurred more often in “H. ducreyi”. Phages from Aggregatibacter actinomycetemcomitans preferably lysogenized strains of specific serotype. Prophage patterns shared by subspecies clades of different bacterial species suggest similar ecoevolutionary drivers. Changes in frequencies of DNA uptake signal sequences and guanine–cytosine content reflect phage-host long-term coevolution. Aggregatibacter and Haemophilus phages were prevalent at multiple oral sites. Together, these findings should help exploring the ecoevolutionary forces shaping virus-host interactions in the human microbiome. Putative lytic phages, especially phiKZ-like, may provide new therapeutic options.

Whole metagenomic shotgun sequencing of the subgingival microbiome of diabetics and non-diabetics with different periodontal conditions

OBJECTIVE

The aim of this study was to use high-resolution whole metagenomic shotgun sequencing to characterize the subgingival microbiome of patients with/without type 2 Diabetes Mellitus and with/without periodontitis.

DESIGN

Twelve subjects, falling into one of the four study groups based on the presence/absence of poorly controlled type 2 Diabetes Mellitus and moderate-severe periodontitis, were selected. For each eligible subject, subgingival plaque samples were collected at 4 sites, all representative of the periodontal condition of the individual (i.e., non-bleeding sulci in subjects without a history of periodontitis, bleeding pockets in patients with moderate-severe periodontitis). The subgingival microbiome was evaluated using high-resolution whole metagenomic shotgun sequencing.

RESULTS

The results showed that: (i) the presence of type 2 Diabetes Mellitus and/or periodontitis were associated with a tendency of the subgingival microbiome to decrease in richness and diversity; (ii) the presence of type 2 Diabetes Mellitus was not associated with significant differences in the relative abundance of one or more species in patients either with or without periodontitis; (iii) the presence of periodontitis was associated with a significantly higher relative abundance of Anaerolineaceae bacterium oral taxon 439 in type 2 Diabetes Mellitus patients.

CONCLUSIONS

Whole metagenomic shotgun sequencing of the subgingival microbiome was extremely effective in the detection of low-abundant taxon. Our results point out a significantly higher relative abundance of Anaerolineaceae bacterium oral taxon 439 in patients with moderate to severe periodontitis vs patients without history of periodontitis, which was maintained when the comparison was restricted to type 2 diabetics.

Microbiome Profiles of Ligature-Induced Periodontitis in Nonhuman Primates across the Life Span

This investigation compared the microbiomes colonizing teeth during the initiation, progression, and resolution of periodontitis in nonhuman primates (Macaca mulatta) at different ages. Subgingival plaque samples were collected at baseline; 0.5, 1, and 3 months following ligature-induced periodontitis; and following naturally occurring disease resolution at 5 months. Samples were analyzed using 16S amplicon sequencing to identify bacterial profiles across age groups: young (<3 years of age), adolescent (3 to 7 years), adult (12 to 15 years), and aged (17 to 23 years). α-Diversity of the microbiomes was greater in the adult/aged samples than in the young/adolescent samples. β-Diversity of the samples demonstrated clear age group differences, albeit individual variation in microbiomes between animals within the age categories was noted. Phylum distributions differed between the young/adolescent animals and the adult/aged animals at each of the time points, showing an enrichment of the phyla Spirochetes, Fusobacteria, and Bacteroidetes associated with periodontitis. Major differences in the top 50 operational taxonomic units (OTUs) were noted in the young and adolescent microbiomes during initiation and progression postligation compared to the adult and aged animals. The proportions of a large number of species in the top 50 OTUs were lower at baseline and in resolved disease microbiomes in the young samples, while profiles in adolescent animals were more consistent with the disease microbiomes. Microbiome profiles for resolution for adults and aged animals appeared more resilient and generally maintained a pattern similar to that of disease. Use of the model can expand our understanding of the crucial interactions of the oral microbiome and host responses in periodontitis.

Comparison of Subgingival and Buccal Mucosa Microbiome in Chronic and Aggressive Periodontitis: A Pilot Study

Periodontal microorganisms not only colonize subgingival pockets, but also are detected on various mucous membranes in patients with periodontitis. The object of this pilot study was, using the next-generation sequencing of 16S RNA gene, to characterize the microbiota in two oral habitats (buccal mucosas and subgingival pockets) in patients with different forms of periodontitis. Thirty-two buccal swab samples and 113 subgingival samples were obtained from eleven subjects with chronic periodontitis (ChP), twelve subjects with aggressive periodontitis (AgP), and nine periodontally healthy individuals (HP). Using Miseq Sequencing of 16S rRNA gene, we found that the subgingival and buccal mucosa microbiome of ChP and AgP patients both differed from HP. Meanwhile, Veillonella, Treponema, Filifactor, Fretibacterium, Peptostreptococcaceae_[XI][G-6], Peptostreptococcaceae_[XI][G-5], Bacteroidetes_[G-5], Bacteroidetes_[G-3], Peptostreptococcaceae_[XI][G-4], Peptostreptococcaceae_[XI][G-2] significantly increased both in buccal and subgingival plaque samples in periodontitis subjects (ChP and AgP) compared with HP. Moreover, the results based on the Unweighted UniFrac distance showed that buccal and subgingival plaque samples from the same individuals show higher community divergence than same habitats from different subject samples. This study demonstrated that the microbiome of buccal mucosa can be influenced by periodontitis. However, subgingival and buccal mucosa microbiome seem to be characterized by species-specific colonization patterns. This pilot study provides a glimpse at the changes of subgingival and buccal mucosa associated with periodontitis from a holistic view. Further studies should be taken to illuminate the interplay between these detected changes and periodontitis development.

Comparison of the oral microbiome of patients with generalized aggressive periodontitis and periodontitis-free subjects

OBJECTIVE

The primary objectives of the study were to assess differences in complex subgingival bacterial composition between periodontitis-free persons and patients with generalized aggressive periodontitis (gAgP).

BACKGROUND

The composition of the oral microbiota plays an important role for both oral and systemic diseases. However, the complex nature of the oral microbiome and its homeostasis is still poorly understood.

MATERIAL AND METHODS

We compared the microbiome of 13 periodontitis-free persons to 13 patients with gAgP. The 16S rRNA genes were amplified, targeting the V3/V4 region using the MiSeq platform.

RESULTS

In total, 1713 different bacterial species were mapped according to the Greengenes database. Using the Shannon index, no significant differences in alpha diversity were found between the two study groups. In principal component and linear discriminant analyses, disease-specific differences in beta diversity of the microbiome composition were evaluated. Bacteroidetes, Spirochaetes, and Synergistetes were more abundant in gAgP whereas Proteobacteria, Firmicutes, and Actinobacteria were associated with a healthy periodontium. At the bacterial species level, we showed that Porphyromonas gingivalis is the strongest indicator of gAgP. Treponema denticola and Tanerella forsythia of the "red complex" as well as Filifactor alocis were among the ten best biomarkers for gAgP.

CONCLUSIONS

These results broaden our knowledge of disease-specific differences in the microbial community associated with generalized AgP. A more complex view of the composition of the oral microbiome describes the etiology of generalized AgP in more detail. These results could help to individually adapt periodontal therapy in these patients.

Quantitative metaproteomics of medieval dental calculus reveals individual oral health status

The composition of ancient oral microbiomes has recently become accessible owing to advanced biomolecular methods such as metagenomics and metaproteomics, but the utility of metaproteomics for such analyses is less explored. Here, we use quantitative metaproteomics to characterize the dental calculus associated with the remains of 21 humans retrieved during the archeological excavation of the medieval (ca. 1100-1450 CE) cemetery of Tjærby, Denmark. We identify 3671 protein groups, covering 220 bacterial species and 81 genera across all medieval samples. The metaproteome profiles of bacterial and human proteins suggest two distinct groups of archeological remains corresponding to health-predisposed and oral disease-susceptible individuals, which is supported by comparison to the calculus metaproteomes of healthy living individuals. Notably, the groupings identified by metaproteomics are not apparent from the bioarchaeological analysis, illustrating that quantitative metaproteomics has the potential to provide additional levels of molecular information about the oral health status of individuals from archeological contexts.