Salivary microbiome profiles of oral cancer patients analyzed before and after treatment.

BACKGROUND: Treating oral squamous cell carcinoma (OSCC) introduces new ecological environments in the oral cavity. This is expected to cause changes in the oral microbiome. The purpose of this study was to gain new information on the salivary microbiome of OSCC patients in order to improve the aftercare of OSCC patients. The aims of this study were to investigate possible changes in the salivary microbiome profiles of OSCC patients before and after cancer treatment and to compare these changes with the profiles of healthy controls. PATIENTS AND METHODS: Paraffin-stimulated whole saliva samples were collected, and the salivary flow rate was measured from 99 OSCC patients prior to surgical resection of the tumor and other adjuvant therapy. After treatment, 28 OSCC patients were re-examined with a mean follow-up time of 48 months. In addition, 101 healthy controls were examined and sampled. After DNA extraction and purification, the V4 hypervariable region of the 16S rRNA gene was amplified and sequenced using Illumina MiSeq. The merged read pairs were denoised using UNOISE3, mapped to zero-radius operational taxonomic units (zOTUs), and the representative zOTU sequences were assigned a taxonomy using HOMD. Descriptive statistics were used to study the differences in the microbial profiles of OSCC patients before and after treatment and in comparison to healthy controls. RESULTS: At baseline, the OSCC patients showed a higher relative abundance of zOTUs classified as Streptococcus anginosus, Abiotrophia defectiva, and Fusobacterium nucleatum. The microbial profiles differed significantly between OSCC patients and healthy controls (F = 5.9, p < 0.001). Alpha diversity of the salivary microbiome of OSCC patients was decreased at the follow-up, and the microbial profiles differed significantly from the pre-treatment (p < 0.001) and from that of healthy controls (p < 0.001). CONCLUSIONS: OSCC patients' salivary microbiome profile had a higher abundance of potentially pathogenic bacteria compared to healthy controls. Treatment of the OSCC caused a significant decrease in alpha diversity and increase in variability of the salivary microbiome, which was still evident after several years of follow-up. OSCC patients may benefit from preventive measures, such as the use of pre- or probiotics, salivary substitutes, or dietary counseling. Video Abstract.

Long-Term Analysis of Resilience of the Oral Microbiome in Allogeneic Stem Cell Transplant Recipients.

Stem cell transplantation (SCT) is associated with oral microbial dysbiosis. However, long-term longitudinal data are lacking. Therefore, this study aimed to longitudinally assess the oral microbiome in SCT patients and to determine if changes are associated with oral mucositis and oral chronic graft-versus-host disease. Fifty allogeneic SCT recipients treated in two Dutch university hospitals were prospectively followed, starting at pre-SCT, weekly during hospitalization, and at 3, 6, 12, and 18 months after SCT. Oral rinsing samples were taken, and oral mucositis (WHO score) and oral chronic graft-versus-host disease (NIH score) were assessed. The oral microbiome diversity (Shannon index) and composition significantly changed after SCT and returned to pre-treatment levels from 3 months after SCT. Oral mucositis was associated with a more pronounced decrease in microbial diversity and with several disease-associated genera, such as Mycobacterium, Staphylococcus, and Enterococcus. On the other hand, microbiome diversity and composition were not associated with oral chronic graft-versus-host disease. To conclude, dysbiosis of the oral microbiome occurred directly after SCT but recovered after 3 months. Diversity and composition were related to oral mucositis but not to oral chronic graft-versus-host disease.

The microbiome of dental and peri-implant subgingival plaque during peri-implant mucositis therapy: A randomized clinical trial.

AIM: To assess the microbial effects of mechanical debridement in conjunction with a mouthrinse on sites with peri-implant mucositis and gingivitis. MATERIALS AND METHODS: Eighty-nine patients with peri-implant mucositis were included in a double-blinded, randomized, placebo-controlled trial with mechanical debridement and 1-month use of either delmopinol, chlorhexidine (CHX), or a placebo mouthrinse. Submucosal and subgingival plaque samples of implants and teeth were collected at baseline and after 1 and 3 months, processed for 16S V4 rRNA gene amplicon sequencing, and analysed bioinformatically. RESULTS: The sites with peri-implant mucositis presented with a less diverse and less anaerobic microbiome. Exposure to delmopinol or CHX, but not to the placebo mouthrinse resulted in microbial changes after 1 month. The healthy sites around the teeth harboured a more diverse and more anaerobe-rich microbiome than the healthy sites around the implants. CONCLUSIONS: Peri-implant sites with mucositis harbour ecologically less complex and less anaerobic biofilms with lower biomass than patient-matched dental sites with gingivitis while eliciting an equal inflammatory response. Adjunctive antimicrobial therapy in addition to mechanical debridement does affect both dental and peri-implant biofilm composition in the short term, resulting in a less dysbiotic subgingival biofilm.

Submucosal microbiome of peri-implant sites: A cross-sectional study.

AIM: To study the peri-implant submucosal microbiome in relation to implant disease status, dentition status, smoking habit, gender, implant location, implant system, time of functional loading, probing pocket depth (PPD), and presence of bleeding on probing. MATERIALS AND METHODS: Biofilm samples were collected from the deepest peri-implant site of 41 patients with paper points, and analysed using 16S rRNA gene pyrosequencing. RESULTS: We observed differences in microbial profiles by PPD, implant disease status, and dentition status. Microbiota in deep pockets included higher proportions of the genera Fusobacterium, Prevotella, and Anaeroglobus compared with shallow pockets that harboured more Rothia, Neisseria, Haemophilus, and Streptococcus. Peri-implantitis (PI) sites were dominated by Fusobacterium and Treponema compared with healthy implants and peri-implant mucositis, which were mostly colonized by Rothia and Streptococcus. Partially edentulous (PE) individuals presented more Fusobacterium, Prevotella, and Rothia, whereas fully edentulous individuals presented more Veillonella and Streptococcus. CONCLUSIONS: PPD, implant disease status, and dentition status may affect the submucosal ecology leading to variation in composition of the microbiome. Deep pockets, PI, and PE individuals were dominated by Gram-negative anaerobic taxa.

Manipulation of Saliva-Derived Microcosm Biofilms To Resemble Dysbiotic Subgingival Microbiota.

Periodontitis is a highly prevalent oral inflammatory disease triggered by dysbiotic subgingival microbiota. For the development of microbiome modulators that can reverse the dysbiotic state and reestablish a health-associated microbiota, a high-throughput in vitro multispecies biofilm model is needed. Our aim is to establish a model that resembles a dysbiotic subgingival microbial biofilm by incorporating the major periodontal pathogen Porphyromonas gingivalis into microcosm biofilms cultured from pooled saliva of healthy volunteers. The biofilms were grown for 3, 7, and 10 days and analyzed for their microbial composition by 16S rRNA gene amplicon sequencing as well as measurement of dipeptidyl peptidase IV (DPP4) activity and butyric acid production. The addition of P. gingivalis increased its abundance in saliva-derived microcosm biofilms from 2.7% on day 3 to >50% on day 10, which significantly reduced the Shannon diversity but did not affect the total number of operational taxonomic units (OTUs). The P. gingivalis-enriched biofilms displayed altered microbial composition as revealed by principal-component analysis and reduced interactions among microbial species. Moreover, these biofilms exhibited enhanced DPP4 activity and butyric acid production. In conclusion, by adding P. gingivalis to saliva-derived microcosm biofilms, we established an in vitro pathogen-enriched dysbiotic microbiota which resembles periodontitis-associated subgingival microbiota in terms of increased P. gingivalis abundance and higher DPP4 activity and butyric acid production. This model may allow for investigating factors that accelerate or hinder a microbial shift from symbiosis to dysbiosis and for developing microbiome modulation strategies.IMPORTANCE In line with the new paradigm of the etiology of periodontitis, an inflammatory disorder initiated by dysbiotic subgingival microbiota, novel therapeutic strategies have been proposed targeting reversing dysbiosis and restoring host-compatible microbiota rather than eliminating the biofilms unselectively. Thus, appropriate laboratory models are required to evaluate the efficacy of potential microbiome modulators. In the present study, we used the easily obtainable saliva as an inoculum, spiked the microcosm biofilms with the periodontal pathogen Porphyromonas gingivalis, and obtained a P. gingivalis-enriched microbiota, which resembles the in vivo pathogen-enriched subgingival microbiota in severe periodontitis. This biofilm model circumvents the difficulties encountered when using subgingival plaque as the inoculum and achieves microbiota in a dysbiotic state in a controlled and reproducible manner, which is required for high-throughput and large-scale evaluation of strategies that can potentially modulate microbial ecology.

Dysbiosis of the Oral Ecosystem in Severe Congenital Neutropenia Patients.

PURPOSE: To decipher the underlying immunological mechanisms in predisposition to oral microbial dysbiosis in severe congenital neutropenia (SCN) patients. EXPERIMENTAL DESIGN: Ten SCN patients (5-23 years old) and 12 healthy controls (5-22 years old) are periodontally examined and provided saliva, subgingival plaque, and gingival crevicular fluid (GCF) samples. The SCN patients received oral hygiene therapy and are re-evaluated after 6 months. Antimicrobial peptides HPN1-3 and LL-37 are assessed in saliva by ELISA. Concentration of 30 cytokines is measured in saliva and GCF by human 30-plex panel, while bacterial profiles of saliva and subgingival plaque are assessed using 16S rDNA amplicon sequencing. RESULTS: There is no significant difference in salivary HPN1-3 and LL-37 concentration between the SCN patients and controls. At baseline, clinical, immunological, and microbiological parameters of the patients are indicative of oral ecological dysbiosis. The SCN patients have significantly higher bleeding on probing (BOP)%, GCF volume, and cytokine levels, high bacterial load with low bacterial diversity in saliva. The associations between the microbiome and immunological parameters in the SCN patients differ from those in the healthy individuals. CONCLUSIONS AND CLINICAL RELEVANCE: SCN patients have a dysregulated immune response toward commensal oral microbiota, which could be responsible for the observed clinical and microbiological signs of dysbiosis.

Microbial changes in relation to oral mucositis in autologous hematopoietic stem cell transplantation recipients.

The aim of this prospective, two center study was to investigate the dynamics of the microbial changes in relation to the development of ulcerative oral mucositis in autologous SCT (autoSCT) recipients. Fifty-one patients were diagnosed with multiple myeloma and treated with high-dose melphalan followed by autoSCT. They were evaluated before, three times weekly during hospitalization, and three months after autoSCT. At each time point an oral rinse was collected and the presence or absence of ulcerative oral mucositis (UOM) was scored (WHO scale). Oral microbiome was determined by using 16S rRNA amplicon sequencing and fungal load by qPCR. Twenty patients (39%) developed UOM. The oral microbiome changed significantly after autoSCT and returned to pre-autoSCT composition after three months. However, changes in microbial diversity and similarity were more pronounced and rapid in patients who developed UOM compared to patients who did not. Already before autoSCT, different taxa discriminated between the 2 groups, suggesting microbially-driven risk factors. Samples with high fungal load (>0.1%) had a significantly different microbial profile from samples without fungi. In conclusion, autoSCT induced significant and reversible changes in the oral microbiome, while patients who did not develop ulcerative oral mucositis had a more resilient microbial ecosystem.

Subgingival microbiome of rheumatoid arthritis patients in relation to their disease status and periodontal health.

OBJECTIVE: Rheumatoid arthritis (RA) and periodontitis are chronic inflammatory diseases that share common risk factors. However, the bidirectional relationship between RA and periodontal disease is not fully understood. This study was undertaken to describe the bacterial component of the subgingival microbiome in RA patients and to relate this to RA disease activity and periodontal status. METHODS: Patients with chronic established RA (N = 78) were periodontally examined and their subgingival plaque samples were collected; their clinical and laboratory data on RA status and medication were obtained from medical records. Bacterial DNA was quantified by universal 16S rDNA qPCR, and Porphyromonas gingivalis by species-specific qPCR. For microbiome assessment, 16S rDNA amplicon sequencing was performed. RESULTS: Active RA was diagnosed in 58% of the patients and periodontitis in 82% (mild: 9%, moderate: 55%, severe: 18%). P. gingivalis was present in 14% of the samples. Different levels of gingival bleeding, periodontal probing depth, RA disease status, prednisolone use and smoking were associated with significantly different microbiome compositions. Two subgingival microbial community types were discerned. CONCLUSION: In RA patients with active disease, anti-inflammatory medication as part of RA therapy was associated with better oral health status and a healthier subgingival microbiome compared to that of RA patients in remission, especially those in remission who were current smokers. RA patients in remission with current smoking status may particularly benefit from a systematic periodontal treatment program. The potential role of microbial community types in patient stratification and personalized therapy should be assessed in longitudinal studies.

Same Exposure but Two Radically Different Responses to Antibiotics: Resilience of the Salivary Microbiome versus Long-Term Microbial Shifts in Feces.

UNLABELLED: Due to the spread of resistance, antibiotic exposure receives increasing attention. Ecological consequences for the different niches of individual microbiomes are, however, largely ignored. Here, we report the effects of widely used antibiotics (clindamycin, ciprofloxacin, amoxicillin, and minocycline) with different modes of action on the ecology of both the gut and the oral microbiomes in 66 healthy adults from the United Kingdom and Sweden in a two-center randomized placebo-controlled clinical trial. Feces and saliva were collected at baseline, immediately after exposure, and 1, 2, 4, and 12 months after administration of antibiotics or placebo. Sequences of 16S rRNA gene amplicons from all samples and metagenomic shotgun sequences from selected baseline and post-antibiotic-treatment sample pairs were analyzed. Additionally, metagenomic predictions based on 16S rRNA gene amplicon data were performed using PICRUSt. The salivary microbiome was found to be significantly more robust, whereas the antibiotics negatively affected the fecal microbiome: in particular, health-associated butyrate-producing species became strongly underrepresented. Additionally, exposure to different antibiotics enriched genes associated with antibiotic resistance. In conclusion, healthy individuals, exposed to a single antibiotic treatment, undergo considerable microbial shifts and enrichment in antibiotic resistance in their feces, while their salivary microbiome composition remains unexpectedly stable. The health-related consequences for the gut microbiome should increase the awareness of the individual risks involved with antibiotic use, especially in a (diseased) population with an already dysregulated microbiome. On the other hand, understanding the mechanisms behind the resilience of the oral microbiome toward ecological collapse might prove useful in combating microbial dysbiosis elsewhere in the body. IMPORTANCE: Many health care professionals use antibiotic prophylaxis strategies to prevent infection after surgery. This practice is under debate since it enhances the spread of antibiotic resistance. Another important reason to avoid nonessential use of antibiotics, the impact on our microbiome, has hardly received attention. In this study, we assessed the impact of antibiotics on the human microbial ecology at two niches. We followed the oral and gut microbiomes in 66 individuals from before, immediately after, and up to 12 months after exposure to different antibiotic classes. The salivary microbiome recovered quickly and was surprisingly robust toward antibiotic-induced disturbance. The fecal microbiome was severely affected by most antibiotics: for months, health-associated butyrate-producing species became strongly underrepresented. Additionally, there was an enrichment of genes associated with antibiotic resistance. Clearly, even a single antibiotic treatment in healthy individuals contributes to the risk of resistance development and leads to long-lasting detrimental shifts in the gut microbiome.