Peri-implantitis caused by multispecies biofilms is a major complication in dental implant treatment. The bacterial infection surrounding dental implants can lead to bone loss and, in turn, to implant failure. A promising strategy to prevent these common complications is the development of implant surfaces that inhibit biofilm development. A reproducible and easy-to-use biofilm model as a test system for large scale screening of new implant surfaces with putative antibacterial potency is therefore of major importance. In the present study, we developed a highly reproducible in vitro four-species biofilm model consisting of the highly relevant oral bacterial species Streptococcus oralis, Actinomyces naeslundii, Veillonella dispar and Porphyromonas gingivalis. The application of live/dead staining, quantitative real time PCR (qRT-PCR), scanning electron microscopy (SEM) and urea-NaCl fluorescence in situ hybridization (urea-NaCl-FISH) revealed that the four-species biofilm community is robust in terms of biovolume, live/dead distribution and individual species distribution over time. The biofilm community is dominated by S. oralis, followed by V. dispar, A. naeslundii and P. gingivalis. The percentage distribution in this model closely reflects the situation in early native plaques and is therefore well suited as an in vitro model test system. Furthermore, despite its nearly native composition, the multispecies model does not depend on nutrient additives, such as native human saliva or serum, and is an inexpensive, easy to handle and highly reproducible alternative to the available model systems. The 96-well plate format enables high content screening for optimized implant surfaces impeding biofilm formation or the testing of multiple antimicrobial treatment strategies to fight multispecies biofilm infections, both exemplary proven in the manuscript.
BackgroundTo investigate the microbial composition of biofilms at inflamed peri-implant and periodontal tissues in the same subject, using 16S rRNA sequencing.MethodsSupra- and submucosal, and supra- and subgingival plaque samples were collected from 7 subjects suffering from diseased peri-implant and periodontal tissues. Bacterial DNA was isolated and 16S rRNA genes were amplified, sequenced and aligned for the identification of bacterial genera.Results43734 chimera-depleted, denoised sequences were identified, corresponding to 1 phylum, 8 classes, 10 orders, 44 families and 150 genera. The most abundant families or genera found in supramucosal or supragingival plaque were Streptoccocaceae, Rothia and Porphyromonas. In submucosal plaque, the most abundant family or genera found were Rothia, Streptococcaceae and Porphyromonas on implants. The most abundant subgingival bacteria on teeth were Prevotella, Streptococcaceae, and TG5. The number of sequences found for the genera Tannerella and Aggregatibacter on implants differed significantly between supra- and submucosal locations before multiple testing. The analyses demonstrated no significant differences between microbiomes on implants and teeth in supra- or submucosal and supra- or subgingival biofilms.ConclusionDiseased peri-implant and periodontal tissues in the same subject share similiar bacterial genera and based on the analysis of taxa on a genus level biofilm compositions may not account for the potentially distinct pathologies at implants or teeth.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6831-14-157) contains supplementary material, which is available to authorized users.
Since the introduction of modern dental implants in the 1980s, the number of inserted implants has steadily increased. Implant systems have become more sophisticated and have enormously enhanced patients’ quality of life. Although there has been tremendous development in implant materials and clinical methods, bacterial infections are still one of the major causes of implant failure. These infections involve the formation of sessile microbial communities, called biofilms. Biofilms possess unique physical and biochemical properties and are hard to treat conventionally. There is a great demand for innovative methods to functionalize surfaces antibacterially, which could be used as the basis of new implant technologies. Present, there are few test systems to evaluate bacterial growth on these surfaces under physiological flow conditions. We developed a flow chamber model optimized for the assessment of dental implant materials. As a result it could be shown that biofilms of the five important oral bacteria Streptococcus gordonii, Streptococcus oralis, Streptococcus salivarius, Porphyromonas gingivalis, and Aggregatibacter actinomycetemcomitans, can be reproducibly formed on the surface of titanium, a frequent implant material. This system can be run automatically in combination with an appropriate microscopic device and is a promising approach for testing the antibacterial effect of innovative dental materials.
The long-term success of osseointegrated oral implants is endangered by inflammation of peri-implant hard and soft tissues caused by bacterial biofilms that may have been initiated by bacterial transmission from the adjacent dentition. The present study aimed to compare the bacterial communities at inflamed implant and tooth sites by broad-range PCR techniques to evaluate the etiological processes of peri-implant and periodontal diseases and potential future therapeutic strategies. Eighteen samples of peri-implant and periodontal microflora were collected from nine partially edentulous patients with implant-retained crowns or bridges revealing clinical signs of gingivitis or mucositis. The clinical parameters plaque index (PI), probing depth (PD), and bleeding on probing were recorded. Amplified fragments of bacterial 16S rRNA genes were separated by use of single-strand conformation polymorphism analysis, and sequences were determined to identify the predominant bacterial genera. The clinical parameters PI and PD were significantly different at implants (PI = 0.4 ± 0.7, PD = 3.1 ± 0.6 mm) compared with teeth (PI = 1.8 ± 0.8, PD = 2.5 ± 0.2 mm). A total of 20 different genera were found at the inflamed tooth and implant sites. The microbial diversity of the microflora surrounding the remaining dentition (12.0 ± 3.8) was significantly higher (p = 0.01) than the diversity of the peri-implant microflora at implant-retained crowns or bridges (6.3 ± 2.3). Within the limitations of the present study, the microbial diversity of the investigated implants and teeth with clinical signs of mucositis or gingivitis exhibits substantial differences, demonstrating that transmission of the complete bacterial microflora from teeth to implants could be excluded. Furthermore, broad-range molecular biological detection methods specify bacterial genera and species in the peri-implant and periodontal microflora which were not in the focus of research interests so far.
Late implant failures, caused by the inflammation of surrounding tissues are a problem in implant dentistry. The path of bacterial transmission from teeth to implants is not completely understood. Therefore, the purpose of this study was to analyze intraindividual bacterial transmission characterizing subgingival microbiomes in teeth and implants, both in healthy subjects and in those with signs of periodontitis or peri-implantitis. Samples of peri-implant and dental sulcus fluid were collected. To identify the predominant microbiota, amplified fragments of bacterial 16S rRNA gene were separated by single strand conformation polymorphism analysis, sequenced and taxonomically classified. A total of 25 different predominant genera were found in the diseased group and 14 genera in the healthy group. Species richness did not differ significantly between implants, neighboring teeth and teeth with largest probing depth in the diseased group. Additionally, no differences between teeth and implants in the healthy group were detected. In contrast, microbial diversity varied between the different sampling points. Species richness is similar in healthy and diseased sites, but the composition of the bacterial community differed within the individual subjects. The underlying analyses strongly suggest that complete transmission from neighboring teeth to implants is unlikely.
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