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.

Antibiotics are often used in the treatment of chronic periodontitis, which is a major cause of tooth loss. However, evidence in favour of a microbial indication for the prescription of antibiotics is lacking, which may increase the risk of the possible indiscriminate use of antibiotics, and consequent, microbial resistance. Here, using an open-ended technique, we report the changes in the subgingival microbiome up to one year post-treatment of patients treated with basic periodontal therapy with or without antibiotics. Antibiotics resulted in a greater influence on the microbiome 3 months after therapy, but this difference disappeared at 6 months. Greater microbial diversity, specific taxa and certain microbial co-occurrences at baseline and not the use of antibiotics predicted better clinical treatment outcomes. Our results demonstrate the predictive value of specific subgingival bacterial profiles for the decision to prescribe antibiotics in the treatment of periodontitis, but they also indicate the need for alternative therapies based on ecological approaches.

Background: High-speed dental instruments produce aerosols, which can contribute to the transmission of pathogenic microorganisms. The aim of this study is to describe the microbial load andcomposition and spatial distribution of aerosols in dental clinics. Methods: In four dental clinics active and passive sampling methods were used before, during and after treatment and at different locations. Retrieved colony forming units (CFU) were sequenced for taxon identification. Results: The samples contained up to 655 CFU/plate/30 minutes and 418 CFU/m 3 /30 minutes during dental treatment for active and passive sampling, respectively. The level of contamination after treatment and at 1.5 m distance from the patient's head was similar to the start of the day. The highest contamination was found at the patient's chest area. The aerosols consisted of 52 different taxa from human origin and 36 from water. Conclusion: Contamination in dental clinics due to aerosols is mainly low, although high level of contamination with taxa from both human and water origin was found within 80 cm around the head of the patient. Our results stress the importance of infection control measures on surfaces in close proximity to the head of the patient as well as in dental water lines.

The purpose of the study was to assess the effect of ciprofloxacin (500 mg twice daily for 10 days) or clindamycin (150 mg 4 times daily for 10 days) on the fecal microbiota of healthy humans for a period of 1 year as compared to placebo. Two different methods, culture and microbiome analysis, were used. Fecal samples were collected for analyses at 6 time-points. The interval needed for the normal microbiota to be normalized after ciprofloxacin or clindamycin treatment differed for various bacterial species. It took 1-12 months to normalize the human microbiota after antibiotic administration, with the most pronounced effect on day 11. Exposure to ciprofloxacin or clindamycin had a strong effect on the diversity of the microbiome, and changes in microbial composition were observed until the 12th month, with the most pronounced microbial shift at month 1. No Clostridium difficile colonization or C. difficile infections were reported. Based on the pyrosequencing results, it appears that clindamycin has more impact than ciprofloxacin on the intestinal microbiota.

ObjectivesThe composition of dental plaque has been well defined, whereas currently there is limited understanding of the composition of denture plaque and how it directly influences denture related stomatitis (DS). The aims of this study were to compare the microbiomes of denture wearers, and to understand the implications of these towards inter-kingdom and host-pathogen interactions within the oral cavity.MethodsSwab samples were obtained from 123 participants wearing either a complete or partial denture; the bacterial composition of each sample was determined using bar-coded illumina MiSeq sequencing of the bacterial hypervariable V4 region of 16S rDNA. Sequencing data processing was undertaken using QIIME, clustered in Operational Taxonomic Units (OTUs) and assigned to taxonomy. The dentures were sonicated to remove the microbial flora residing on the prosthesis, sonicate was then cultured using diagnostic colorex Candida media. Samples of unstimulated saliva were obtained and antimicrobial peptides (AMP) levels were measured by ELISA.ResultsWe have shown that dental and denture plaques are significantly distinct both in composition and diversity and that the oral microbiome composition of a denture wearer is variable and is influenced by the location within the mouth. Dentures and mucosa were predominantly made up of Bacilli and Actinobacteria. Moreover, the presence of natural teeth has a significant impact on the overall microbial composition, when compared to the fully edentulous. Furthermore, increasing levels of Candida spp. positively correlate with Lactobacillus spp. AMPs were quantified, though showed no specific correlations.ConclusionsThis is the first study to provide a detailed understanding of the oral microbiome of denture wearers and has provided evidence that DS development is more complex than simply a candidal infection. Both fungal and bacterial kingdoms clearly play a role in defining the progression of DS, though we were unable to show a defined role for AMPs.

While the aesthetic effect of orthodontic treatment is clear, the knowledge on how it influences the oral microbiota and the consequential effects on oral health are limited. In this randomized controlled clinical trial we investigated the changes introduced in the oral ecosystem, during and after orthodontic treatment with fixed appliances in combination with or without a fluoride mouthwash, of 10–16.8 year old individuals (N = 91). We followed several clinical parameters in time, in combination with microbiome changes using next-generation sequencing of the bacterial 16S rRNA gene. During the course of our study, the oral microbial community displayed remarkable resilience towards the disturbances it was presented with. The effects of the fluoride mouthwash on the microbial composition were trivial. More pronounced microbial changes were related to gingival health status, orthodontic treatment and time. Periodontal pathogens (e.g. Selenomonas and Porphyromonas) were highest in abundance during the orthodontic treatment, while the health associated Streptococcus, Rothia and Haemophilus gained abundance towards the end and after the orthodontic treatment. Only minor compositional changes remained in the oral microbiome after the end of treatment. We conclude that, provided proper oral hygiene is maintained, changes in the oral microbiome composition resulting from orthodontic treatment are minimal and do not negatively affect oral health.

Currently there are no evidence-based ecological measures for prevention of overgrowth and subsequent infection by fungi in the oral cavity. The aim of this study was to increase our knowledge on fungal–bacterial ecological interactions. Salivary Candida abundance of 82 Dutch adults aged 58–80 years was established relative to the bacterial load by quantitative PCR analysis of the Internal Transcribed (ITS) region (Candida) and 16S rDNA gene (bacteria). The salivary microbiome was assessed using barcoded pyrosequencing of the bacterial hypervariable regions V5–V7 of 16S rDNA. Sequencing data was preprocessed by denoising and chimera removal, clustered in Operational Taxonomic Units (OTUs) and assigned to taxonomy. Both OTU-based (PCA, diversity statistics) and phylogeny-based analyses (UniFrac, PCoA) were performed. Saliva of Dutch older adults contained 0–4 × 108 CFU/mL Candida with a median Candida load of 0.06%. With increased Candida load the diversity of the salivary microbiome decreased significantly (p<0.001). Increase in the Candida load correlated positively with class Bacilli, and negatively with class Fusobacteria, Flavobacteria, and Bacteroidia. Microbiomes with high Candida load were less diverse and had a distinct microbial composition towards dominance by saccharolytic and acidogenic bacteria - streptococci. The control of the acidification of the oral environment may be a potential preventive measure for Candida outgrowth that should be evaluated in longitudinal clinical intervention trials.

With this review, we aim to increase the quality standards for clinical studies with microbiome as an output parameter. We critically address the existing body of evidence for good quality practices in oral microbiome studies based on 16S rRNA gene amplicon sequencing. First, we discuss the usefulness of microbiome profile analyses. Is a microbiome study actually the best approach for answering the research question? This is followed by addressing the criteria for the most appropriate study design, sample size, and the necessary data (study metadata) that should be collected. Next, we evaluate the available evidence for best practices in sample collection, transport, storage, and DNA isolation. Finally, an overview of possible sequencing options (eg, 16S rRNA gene hypervariable regions, sequencing platforms), processing and data interpretation approaches, as well as requirements for meaningful data storage, sharing, and reporting are provided.