Egija Zaura

Pyrosequencing analysis of the Oral Microflora of healthy adults

A good definition of commensal microflora and an understanding of its relation to health are essential in preventing and combating disease. We hypothesized that the species richness of human oral microflora is underestimated. Saliva and supragingival plaque were sampled from 71 and 98 healthy adults, respectively. Amplicons from the V6 hypervariable region of the small-subunit ribosomal RNA gene were generated by PCR, pooled into saliva and plaque pools, and sequenced by means of the Genome Sequencer 20 system at 454 Life Sciences. Data were evaluated by taxonomic and rarefaction analyses. The 197,600 sequences generated yielded about 29,000 unique sequences, representing 22 taxonomic phyla. Grouping the sequences in operational taxonomic units (6%) yielded 3621 and 6888 species-level phylotypes in saliva and plaque, respectively. This work gives a radically new insight into the diversity of human oral microflora, which, with an estimated number of 19,000 phylotypes, is considerably higher than previously reported.

Exploring the oral microbiota of children at various developmental stages of their dentition in the relation to their oral health

BackgroundAn understanding of the relation of commensal microbiota to health is essential in preventing disease. Here we studied the oral microbial composition of children (N = 74, aged 3 - 18 years) in natural transition from their deciduous to a permanent dentition and related the microbial profiles to their oral health status. The microbial composition of saliva was assessed by barcoded pyrosequencing of the V5-V6 hypervariable regions of the 16 S rRNA, as well as by using phylogenetic microarrays.ResultsPyrosequencing reads (126174 reads, 1045 unique sequences) represented 8 phyla and 113 higher taxa in saliva samples. Four phyla - Firmicutes, Bacteriodetes, Proteobacteria and Actinobacteria - predominated in all groups. The deciduous dentition harboured a higher proportion of Proteobacteria (Gammaproteobacteria, Moraxellaceae) than Bacteroidetes, while in all other groups Bacteroidetes were at least as abundant as Proteobacteria. Bacteroidetes (mainly genus Prevotella), Veillonellaceae family, Spirochaetes and candidate division TM7 increased with increasing age, reflecting maturation of the microbiome driven by biological changes with age.Microarray analysis enabled further analysis of the individual salivary microbiota. Of 350 microarray probes, 156 gave a positive signal with, on average, 77 (range 48-93) probes per individual sample.A caries-free oral status significantly associated with the higher signal of the probes targeting Porphyromonas catoniae and Neisseria flavescens.ConclusionsThe potential role of P. catoniae and N. flavescens as oral health markers should be assessed in large-scale clinical studies. The combination of both, open-ended and targeted molecular approaches provides us with information that will increase our understanding of the interplay between the human host and its microbiome.

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

ABSTRACT 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. 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.

Acquiring and maintaining a normal oral microbiome: current perspective

The oral microbiota survives daily physical and chemical perturbations from the intake of food and personal hygiene measures, resulting in a long-term stable microbiome. Biological properties that confer stability in the microbiome are important for the prevention of dysbiosis—a microbial shift toward a disease, e.g., periodontitis or caries. Although processes that underlie oral diseases have been studied extensively, processes involved in maintaining of a normal, healthy microbiome are poorly understood. In this review we present our hypothesis on how a healthy oral microbiome is acquired and maintained. We introduce our view on the prenatal development of tolerance for the normal oral microbiome: we propose that development of fetal tolerance toward the microbiome of the mother during pregnancy is the major factor for a successful acquisition of a normal microbiome. We describe the processes that influence the establishment of such microbiome, followed by our perspective on the process of sustaining a healthy oral microbiome. We divide microbiome-maintenance factors into host-derived and microbe-derived, while focusing on the host. Finally, we highlight the need and directions for future research.

The Relation between Oral Candida Load and Bacterial Microbiome Profiles in Dutch Older Adults

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.

Ecology of the microbiome of the infected root canal system: a comparison between apical and coronal root segments

AIM To evaluate the microbial ecology of the coronal and apical segments of infected root canal systems using a complete sampling technique and next-generation sequencing. METHODOLOGY The roots of 23 extracted teeth with apical periodontitis were sectioned in half, horizontally, and cryo-pulverized. Bacterial communities were profiled using tagged 454 pyrosequencing of the 16S rDNA hypervariable V5-V6 region. RESULTS The sequences were classified into 606 taxa (species or higher taxon), representing 24 bacterial phyla or candidate divisions and one archaeal phylum. Proteobacteria were more abundant in the apical samples (P < 0.05), whilst Actinobacteria were in significantly higher proportions in the coronal samples. The apical samples harboured statistically significantly more taxa than the coronal samples (P = 0.01) and showed a higher microbial diversity. Several taxa belonging to fastidious obligate anaerobes were significantly more abundant in the apical segments of the roots compared with their coronal counterparts. CONCLUSIONS Endodontic infections are more complex than reported previously. The apical part of the root canal system drives the selection of a more diverse and more anaerobic community than the coronal part. The presence of a distinct ecological niche in the apical region explains the difficulty of eradication of the infection and emphasizes the need for new treatment approaches to be developed.

Subgingival microbiome in smokers and non-smokers in periodontitis: an exploratory study using traditional targeted techniques and a next-generation sequencing

AIM To compare the results of two targeted techniques to an open-ended technique in periodontitis patients, differentiated on the basis of smoking habit. MATERIALS & METHODS Thirty periodontitis patients (15 smokers and 15 non-smokers) provided subgingival plaque samples for 16S rRNA gene amplicon sequencing, culturing and quantitative polymerase chain reaction (qPCR). RESULTS No differences were found in the composition of the subgingival microbiome between smokers and non-smokers with culture and qPCR. With pyrosequencing, operational taxonomic units (OTUs) classified to genera Fusobacterium, Prevotella and Selenomonas were more abundant in smokers, while OTUs belonging to the genera Peptococcus and Capnocytophaga were more abundant in non-smokers. Principal coordinate analysis identified two clusters; one was composed mainly of smokers (80%) and revealed significantly lower taxonomic diversity, higher attachment loss and higher proportion of the genera Fusobacterium, Paludibacter and Desulfobubus. CONCLUSION In periodontitis, there is a difference in the composition of the subgingival microbiome between smokers and non-smokers, as revealed by pyrosequencing. This difference was not identified by the targeted techniques. Low taxonomic diversity was associated with higher disease severity, especially in smokers. This supports the hypothesis of the ecological microbial-host interaction in the severity of periodontal disease.

Comparing clustering and pre-processing in taxonomy analysis

MOTIVATION Massively parallel sequencing allows for rapid sequencing of large numbers of sequences in just a single run. Thus, 16S ribosomal RNA (rRNA) amplicon sequencing of complex microbial communities has become possible. The sequenced 16S rRNA fragments (reads) are clustered into operational taxonomic units and taxonomic categories are assigned. Recent reports suggest that data pre-processing should be performed before clustering. We assessed combinations of data pre-processing steps and clustering algorithms on cluster accuracy for oral microbial sequence data. RESULTS The number of clusters varied up to two orders of magnitude depending on pre-processing. Pre-processing using both denoising and chimera checking resulted in a number of clusters that was closest to the number of species in the mock dataset (25 versus 15). Based on run time, purity and normalized mutual information, we could not identify a single best clustering algorithm. The differences in clustering accuracy among the algorithms after the same pre-processing were minor compared with the differences in accuracy among different pre-processing steps. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. CONTACT bonder.m.j@gmail.com or b.brandt@acta.nl

Historical and contemporary hypotheses on the development of oral diseases: are we there yet?

Dental plaque is an oral biofilm that much like the rest of our microbiome has a role in health and disease. Specifically, it is the cause of very common oral diseases such as caries, gingivitis, and periodontitis. The ideas about oral disease development have evolved over time. In the nineteenth century, scientists could not identify bacteria related to disease due to the lack of technology. This led to the “Non-Specific Plaque Hypothesis” or the idea that the accumulation of dental plaque was responsible for oral disease without discriminating between the levels of virulence of bacteria. In the twentieth century this idea evolved with the techniques to analyze the changes from health to disease. The first common hypothesis was the “Specific Plaque Hypothesis” (1976) proposing that only a few species of the total microflora are actively involved in disease. Secondly, the “Non-Specific Plaque Hypothesis” was updated (1986) and the idea that the overall activity of the total microflora could lead to disease, was enriched by taking into account difference in virulence among bacteria. Then, a hypothesis was considered that combines key concepts of the earlier two hypotheses: the “Ecological Plaque Hypothesis” (1994), which proposes that disease is the result of an imbalance in the microflora by ecological stress resulting in an enrichment of certain disease-related micro-organisms. Finally, the recent “Keystone-Pathogen Hypothesis” (2012) proposes that certain low-abundance microbial pathogens can cause inflammatory disease by interfering with the host immune system and remodeling the microbiota. In this comprehensive review, we describe how these different hypotheses, and the ideas around them, arose and test their current applicability to the understanding of the development of oral disease. Finally, we conclude that an all-encompassing ecological hypothesis explaining the shifts from health to disease is still lacking.

Intrinsic challenges in ancient microbiome reconstruction using 16S rRNA gene amplification

To date, characterization of ancient oral (dental calculus) and gut (coprolite) microbiota has been primarily accomplished through a metataxonomic approach involving targeted amplification of one or more variable regions in the 16S rRNA gene. Specifically, the V3 region (E. coli 341–534) of this gene has been suggested as an excellent candidate for ancient DNA amplification and microbial community reconstruction. However, in practice this metataxonomic approach often produces highly skewed taxonomic frequency data. In this study, we use non-targeted (shotgun metagenomics) sequencing methods to better understand skewed microbial profiles observed in four ancient dental calculus specimens previously analyzed by amplicon sequencing. Through comparisons of microbial taxonomic counts from paired amplicon (V3 U341F/534R) and shotgun sequencing datasets, we demonstrate that extensive length polymorphisms in the V3 region are a consistent and major cause of differential amplification leading to taxonomic bias in ancient microbiome reconstructions based on amplicon sequencing. We conclude that systematic amplification bias confounds attempts to accurately reconstruct microbiome taxonomic profiles from 16S rRNA V3 amplicon data generated using universal primers. Because in silico analysis indicates that alternative 16S rRNA hypervariable regions will present similar challenges, we advocate for the use of a shotgun metagenomics approach in ancient microbiome reconstructions.