Pyrosequencing of supra- and subgingival biofilms from inflamed peri-implant and periodontal sites

Subjects included in the study had at least ≥30% sites with PD ≥4 mm and evident radiographic bone loss. All patients were partially edentulous (not fewer than 8 teeth), with at least 1 functioning oral implant restored with crowns or prostheses. Inclusion criteria were: (A) one implant and teeth showing signs of active inflammation (tissue with manifest signs of inflammation (redness and swelling), bleeding on probing (BOP) and pocket depth (PD) ≥ 4 mm in at least one site and evidence of radiographic bone loss), (B) implants had to be functioning for at least 1 year. Exclusion criteria were: (A) any peri-implant or periodontal treatment 6 months before sampling. (B) systemic diseases such as diabetes mellitus, (C) smoking, (D) antibiotic or immunosuppressant medication within the previous 3 months.

A comprehensive medical history was recorded, followed by clinical and radiographic examination. Informed consent was obtained and the study was approved by the local Ethics committee of Hannover Medical School (no. 4348).

Two experienced dentists examined all subjects. Pocket depth was measured using a pressure calibrated periodontal probe (Hawe Click-Probe, Kerr Hawe SA, Bioggio, Switzerland). Probing depth was measured to the nearest millimeter on the scale. Bleeding on probing was assessed after probing using a dichotomous measure. All measurements were performed on 4 sites of all implants and teeth. Plaque deposits were recorded (presence/absence) without staining, using a modified Approximal Plaque Index (API) [15].

In each subject, the implant and the tooth with the deepest depths were chosen for plaque collection. After isolating the sampling area with cotton rolls and gentle drying with an air syringe, 2 sterile endodontic paper points (Absorbent Paper Points, VDW GmbH, Munich, Germany) were used supramucosally or supragingivally to collect the biofilms. Subsequently, the residual supramucosal and supragingival plaques were completely removed with a dental scaler. Two sterile paper points were then placed submucosally or subgingivally. The samples were pooled separately for every implant, tooth and location and were placed in 2 ml cryotubes (Eppendorf, Hamburg, Germany) and frozen immediately at -80°C before processing.

From each sample, an approximately 550 bp fragment of the 16S rRNA gene was amplified using the broad range primers 27f (5’-AGAGTTTGATCMTGGCTCAG-3´) and 521r (5’-ACCGCGGCTGCTGGCAC-3’; both Eurogentec, Seraing, Belgium). The primers targeted conserved DNA sequences flanking the V1 and V3 hypervariable regions within the 16S rRNA gene. PCR was performed on a TProfessional thermocycler (Biometra, Göttingen, Germany) in a total reaction volume of 50 μl. The PCR mix contained approximately 20 ng of template DNA, 200 nM of each primer, 1x PCR buffer (including 1.5 mM magnesium chloride; Qiagen, Hilden, Germany), 1.5U HotStar Taq polymerase (Qiagen, Hilden, Germany), 200 mM of each dNTP (Roth, Karlsruhe, Germany) and PCR-grade water (Roche, Penzberg, Germany). PCR conditions were as follows: Initial denaturation at 95°C for 15 min; 32 amplification cycles consisting of denaturation at 94°C for 1 min, annealing at 52°C for 40s, elongation at 72°C for 1 min; final extension at 72°C for 10 min. PCR reactions were separated on a 1.0% agarose gel (Agarose MP; AppliChem, Darmstadt, Germany) and purified using the QIAquick Gel Extraction Kit (Qiagen, Hilden, Germany). The purified amplicons of each sample were used as template for a second PCR step with the primer 27f-AdaB (5’-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGAGAGTTTGATCMTGGCTCAG-3´) and an individual reverse primer 521r-MID_X (5’-CCATCTCATCCCTGCGTGTCTCCGACTCAGXXXXXXXXXXXACCGCGGCTGCTGGCAC-3’; XXXXXXXXXXX = unique MID-tag) containing a unique Multiplex-Identifier (MID) barcode sequence. Amplification chemistry was the same as described above, however, 100 ng of template DNA were used per reaction, the annealing temperature was raised to 67°C and the cycle number was reduced to 15. PCR reaction products were purified by agarose gel electrophoresis and extracted as described before. The DNA concentrations were determined using the AccuBlue™ High Sensitivity dsDNA Quantitation Kit (Biotium, Hayward, USA) in combination with a BioTekSynergy II fluorescence reader (BioTek, Bad Friedrichshall, Germany). Subsequently, the samples were mixed in an equimolar ratio and further processed according to the manufacturer’s instruction for the Titanium Library Preparation Kit (Roche, Penzberg, Germany). Pyrosequencing was performed on a GS FLX sequencer (Roche, Penzberg, Germany).

The sequences were assigned to OTUs with the uclust method in qiime with a similarity threshold of 0.97, which corresponds to genus level OTUs. For the following taxonomic assignment, we used the blast method in qiime with the greengenes 12_10 release with 97% OTUs as the reference database. In addition, genera were categorized according to their Gram staining based on Bergey’s Manual of Systematic Bacteriology.

The OTU-table created by qiime after denoising and chimera checking was imported into the statistical programming language R [18] using the Bioconductor [19] package phyloseq [20]. The following graphical analyses were also performed using the phyloseq package and were created for (a) the whole data set, (b) the implant subset and (c) the tooth subset. The taxonomic rank used for the following analyses was the genus level. First, heat maps for the 50 most abundant bacteria were created. Second, Principal Coordinate Analyses (PCoA) of UniFac distances were calculated and plotted. The inferential statistical analysis was calculated with the Bioconductor package edgeR [21]. Therefore log Fold-Changes and corresponding multiplicity-adjusted p values were estimated from separate generalized linear models for every genus with patient as covariate and considering the paired design character. Biodiversity was calculated using the Shannon-Diversity Index [22].

Seven subjects (2 males, 5 females, mean age 60.1 ± 9.8 years) were eligible for the study between August and October 2010 at Hannover Medical School, Department of Prosthetic Dentistry and Biomedical Materials Science. Individual data and full-mouth scorings of all patients are summarized in Table 1. All implants investigated had been functioning for an average of 11.6 ± 5.5 years. Clinical signs of inflammation were apparent at investigated implants (PD 4.9 ± 1.2 mm, BOP 39.9 ± 34.9 %) and teeth (PD 4.1 ± 1.2 mm, BOP 35.7 ± 31.8%). Differences between the clinical recordings at implants and teeth were not significant (Table 1).

28 supra- and subgingival samples from 7 patients were analyzed and yielded a total of 43734 chimera-depleted, denoised sequences representing 1 phylum, 8 classes, 10 orders, 44 families and 150 genera (Additional file 1). On implants, these sequences represented the families Porphyromonadaceae, Lachnospiraceae, Streptococcaceae and genera Rothia, Actinomyces, Paenibacillus, Microbacterium, Pseudoramibacter, Leptotrichia, Parascardovia, Tannerella, Granulicatella, Tessaracoccus, Clostridium, Aeromonadales, Veillonella, Capnocytophaga, Prevotella, TG5, Fusobacterium, Exiguobacterium, Enterococcus, Porphyromonas, Streptococcus at implants. On teeth, the sequences represented the families Coriobacteriaceae, Rs-045, Veillonellaceae, Neisseriaceae, and the genera Mogibacterium, Porphyromonas, Tannerella, Aggregatibacter, Treponema, Capnocytophaga, Lactococcus, Granulicatella, Enterococcus, Exiguobacterium, Atopobium, Veillonella. On implants and teeth, the above-mentioned bacteria accounted for > 90% of all sequences.

In supramucosal or supragingival plaques on implants and teeth, the most abundant taxa were Streptococcacea, Rothia, and Porphyromonas. In submucosal plaques at implants, the most abundant taxa found were Rothia, Streptococcaceae and Porphyromonas. The most abundant subgingival bacteria on teeth were Prevotella, Streptococcaceae and TG5 (Figure 1a, b).

The statistical analysis showed significant differences between supra- and submucosal plaque on implants for the genus Tannerella (p = 0.0067) and nearly significant differences for the genus Aggregatibacter (p = 0.056). After correction for multiple testing, these differences were no longer significant.

The Gram stain categories on implants and teeth are presented in Figure 2a and b. In general, Gram-positive bacteria were more prevalent than Gram-negative bacteria in all samples. On implants, Gram-positive bacteria were predominately found in supra- and submucosal samples. In supragingival samples of teeth, Gram-positive bacteria were more frequent than Gram-negative bacteria, but in subgingival plaque samples the abundances of Gram-positive and Gram-negative bacteria were similar. On implants and teeth, the number of Gram-negative bacteria were greater at submucosal and subgingival locations than at supramucosal and supragingival sites.

The Principal Coordinate Analysis (Figure 3) of weighted UniFac distances revealed no distinct partitioning of the bacterial communities associated with implants or teeth (p > 0.01).

Data visualization was performed using a heat map display, where the relative abundances of the 50 most frequent genera are represented by different brightnesses (Figure 4). Samples from different locations within individual patients shared only minimal similarities in bacterial community compositions, as shown with hierarchical clustering of bacterial taxa in the heat map display. Communities from supramucosal locations at implants closely clustered with communities from submucosal locations at implants. In contrast, samples taken from supragingival plaque were less similar to subgingival plaque samples at teeth.

The Shannon Diversity index describes the biodiversity and considers the number of genera and their abundances [22]. Neither implants nor teeth demonstrated significant differences in the diversity index for supra- and submucosal locations at implants and supra- or subgingival locations at teeth (Figure 5).