Bart J. F. Keijser

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.

Variability and Diversity of Nasopharyngeal Microbiota in Children: A Metagenomic Analysis

The nasopharynx is the ecological niche for many commensal bacteria and for potential respiratory or invasive pathogens like Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis. Disturbance of a balanced nasopharyngeal (NP) microbiome might be involved in the onset of symptomatic infections with these pathogens, which occurs primarily in fall and winter. It is unknown whether seasonal infection patterns are associated with concomitant changes in NP microbiota. As young children are generally prone to respiratory and invasive infections, we characterized the NP microbiota of 96 healthy children by barcoded pyrosequencing of the V5–V6 hypervariable region of the 16S-rRNA gene, and compared microbiota composition between children sampled in winter/fall with children sampled in spring. The approximately 1000000 sequences generated represented 13 taxonomic phyla and approximately 250 species-level phyla types (OTUs). The 5 most predominant phyla were Proteobacteria (64%), Firmicutes (21%), Bacteroidetes (11%), Actinobacteria (3%) and Fusobacteria (1,4%) with Moraxella, Haemophilus, Streptococcus, Flavobacteria, Dolosigranulum, Corynebacterium and Neisseria as predominant genera. The inter-individual variability was that high that on OTU level a core microbiome could not be defined. Microbiota profiles varied strongly with season, with in fall/winter a predominance of Proteobacteria (relative abundance (% of all sequences): 75% versus 51% in spring) and Fusobacteria (absolute abundance (% of children): 14% versus 2% in spring), and in spring a predominance of Bacteroidetes (relative abundance: 19% versus 3% in fall/winter, absolute abundance: 91% versus 54% in fall/winter), and Firmicutes. The latter increase is mainly due to (Brevi)bacillus and Lactobacillus species (absolute abundance: 96% versus 10% in fall/winter) which are like Bacteroidetes species generally related to healthy ecosystems. The observed seasonal effects could not be attributed to recent antibiotics or viral co-infection. The NP microbiota of young children is highly diverse and appears different between seasons. These differences seem independent of antibiotic use or viral co-infection.

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.

Early Respiratory Microbiota Composition Determines Bacterial Succession Patterns and Respiratory Health in Children

RATIONALE Many bacterial pathogens causing respiratory infections in children are common residents of the respiratory tract. Insight into bacterial colonization patterns and microbiota stability at a young age might elucidate healthy or susceptible conditions for development of respiratory disease. OBJECTIVES To study bacterial succession of the respiratory microbiota in the first 2 years of life and its relation to respiratory health characteristics. METHODS Upper respiratory microbiota profiles of 60 healthy children at the ages of 1.5, 6, 12, and 24 months were characterized by 16S-based pyrosequencing. We determined consecutive microbiota profiles by machine-learning algorithms and validated the findings cross-sectionally in an additional cohort of 140 children per age group. MEASUREMENTS AND MAIN RESULTS Overall, we identified eight distinct microbiota profiles in the upper respiratory tract of healthy infants. Profiles could already be identified at 1.5 months of age and were associated with microbiota stability and change over the first 2 years of life. More stable patterns were marked by early presence and high abundance of Moraxella and Corynebacterium/Dolosigranulum and were positively associated with breastfeeding in the first period of life and with lower rates of parental-reported respiratory infections in the consecutive periods. Less stable profiles were marked by high abundance of Haemophilus or Streptococcus. CONCLUSIONS These findings provide novel insights into microbial succession in the respiratory tract in infancy and link early-life profiles to microbiota stability and respiratory health characteristics. New prospective studies should elucidate potential implications of our findings for early diagnosis and prevention of respiratory infections. Clinical trial registered with www.clinicaltrials.gov (NCT00189020).

Differential Modulation by Akkermansia muciniphila and Faecalibacterium prausnitzii of Host Peripheral Lipid Metabolism and Histone Acetylation in Mouse Gut Organoids

ABSTRACT The gut microbiota is essential for numerous aspects of human health. However, the underlying mechanisms of many host-microbiota interactions remain unclear. The aim of this study was to characterize effects of the microbiota on host epithelium using a novel ex vivo model based on mouse ileal organoids. We have explored the transcriptional response of organoids upon exposure to short-chain fatty acids (SCFAs) and products generated by two abundant microbiota constituents, Akkermansia muciniphila and Faecalibacterium prausnitzii. We observed that A. muciniphila metabolites affect various transcription factors and genes involved in cellular lipid metabolism and growth, supporting previous in vivo findings. Contrastingly, F. prausnitzii products exerted only weak effects on host transcription. Additionally, A. muciniphila and its metabolite propionate modulated expression of Fiaf, Gpr43, histone deacetylases (HDACs), and peroxisome proliferator-activated receptor gamma (Pparγ), important regulators of transcription factor regulation, cell cycle control, lipolysis, and satiety. This work illustrates that specific bacteria and their metabolites differentially modulate epithelial transcription in mouse organoids. We demonstrate that intestinal organoids provide a novel and powerful ex vivo model for host-microbiome interaction studies. IMPORTANCE We investigated the influence of the gut microbiota and microbially produced short-chain fatty acids (SCFAs) on gut functioning. Many commensal bacteria in the gut produce SCFAs, particularly butyrate, acetate, and propionate, which have been demonstrated to reduce the risk of gastrointestinal disorders. Organoids—small crypt-villus structures grown from ileal intestinal stem cells—were exposed to SCFAs and two specific gut bacteria. Akkermansia muciniphila, found in the intestinal mucus, was recently shown to have a favorable effect on the disrupted metabolism associated with obesity. Faecalibacterium prausnitzii is a commensal gut bacterium, the absence of which may be associated with Crohn’s disease. We showed that in our model, A. muciniphila induces stronger effects on the host than F. prausnitzii. We observed that A. muciniphila and propionate affect the expression of genes involved in host lipid metabolism and epigenetic activation or silencing of gene expression. We demonstrated that organoids provide a powerful tool for host-microbe interaction studies. We investigated the influence of the gut microbiota and microbially produced short-chain fatty acids (SCFAs) on gut functioning. Many commensal bacteria in the gut produce SCFAs, particularly butyrate, acetate, and propionate, which have been demonstrated to reduce the risk of gastrointestinal disorders. Organoids—small crypt-villus structures grown from ileal intestinal stem cells—were exposed to SCFAs and two specific gut bacteria. Akkermansia muciniphila, found in the intestinal mucus, was recently shown to have a favorable effect on the disrupted metabolism associated with obesity. Faecalibacterium prausnitzii is a commensal gut bacterium, the absence of which may be associated with Crohn’s disease. We showed that in our model, A. muciniphila induces stronger effects on the host than F. prausnitzii. We observed that A. muciniphila and propionate affect the expression of genes involved in host lipid metabolism and epigenetic activation or silencing of gene expression. We demonstrated that organoids provide a powerful tool for host-microbe interaction studies.

Deep Sequencing Analyses of Low Density Microbial Communities: Working at the Boundary of Accurate Microbiota Detection

Introduction Accurate analyses of microbiota composition of low-density communities (103–104 bacteria/sample) can be challenging. Background DNA from chemicals and consumables, extraction biases as well as differences in PCR efficiency can significantly interfere with microbiota assessment. This study was aiming to establish protocols for accurate microbiota analysis at low microbial density. Methods To examine possible effects of bacterial density on microbiota analyses we compared microbiota profiles of serial diluted saliva and low (nares, nasopharynx) and high-density (oropharynx) upper airway communities in four healthy individuals. DNA was extracted with four different extraction methods (Epicentre Masterpure, Qiagen DNeasy, Mobio Powersoil and a phenol bead-beating protocol combined with Agowa-Mag-mini). Bacterial DNA recovery was analysed by 16S qPCR and microbiota profiles through GS-FLX-Titanium-Sequencing of 16S rRNA gene amplicons spanning the V5–V7 regions. Results Lower template concentrations significantly impacted microbiota profiling results. With higher dilutions, low abundant species were overrepresented. In samples of <105 bacteria per ml, e.g. DNA <1 pg/µl, microbiota profiling deviated from the original sample and other dilutions showing a significant increase in the taxa Proteobacteria and decrease in Bacteroidetes. In similar low density samples, DNA extraction method determined if DNA levels were below or above 1 pg/µl and, together with lysis preferences per method, had profound impact on microbiota analyses in both relative abundance as well as representation of species. Conclusion This study aimed to interpret microbiota analyses of low-density communities. Bacterial density seemed to interfere with microbiota analyses at < than 106 bacteria per ml or DNA <1 pg/µl. We therefore recommend this threshold for working with low density materials. This study underlines that bias reduction is crucial for adequate profiling of especially low-density bacterial communities.

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.

The Impact of Breastfeeding on Nasopharyngeal Microbial Communities in Infants

RATIONALE Breastfeeding elicits significant protection against respiratory tract infections in infancy. Modulation of respiratory microbiota might be part of the natural mechanisms of protection against respiratory diseases induced by breastfeeding. OBJECTIVES To study the association between breastfeeding and nasopharyngeal microbial communities, including all cultivable and noncultivable bacteria. METHODS In this observational study, we analyzed the microbiota of infants that had received exclusive breastfeeding (n = 101) and exclusive formula feeding (n = 101) at age 6 weeks and 6 months by 16S-based GS-FLX-titanium-pyrosequencing. MEASUREMENTS AND MAIN RESULTS At 6 weeks of age the overall bacterial community composition was significantly different between breastfed and formula-fed children (nonmetric multidimensional scaling, P = 0.001). Breastfed children showed increased presence and abundance of the lactic acid bacterium Dolosigranulum (relative effect size [RES], 2.61; P = 0.005) and Corynebacterium (RES, 1.98; P = 0.039) and decreased abundance of Staphylococcus (RES, 0.48; P 0.03) and anaerobic bacteria, such as Prevotella (RES, 0.25; P < 0.001) and Veillonella (RES, 0.33; P < 0.001). Predominance (>50% of the microbial profile) of Corynebacterium and Dolosigranulum was observed in 45 (44.6%) breastfed infants compared with 19 (18.8%) formula-fed infants (relative risk, 2.37; P = 0.006). Dolosigranulum abundance was inversely associated with consecutive symptoms of wheezing and number of mild respiratory tract infections experienced. At 6 months of age associations between breastfeeding and nasopharyngeal microbiota composition had disappeared. CONCLUSIONS Our data suggest a strong association between breastfeeding and microbial community composition in the upper respiratory tract of 6-week-old infants. Observed differences in microbial community profile may contribute to the protective effect of breastfeeding on respiratory infections and wheezing in early infancy. Clinical trial registered with www.clinicaltrials.gov (NCT 00189020).

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.