Abstract
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.
Highlights
Dental implants play an important role in maintaining full oral function after tooth loss [1]
Using an array of different methods, including confocal laser scanning microscopy (CLSM), scanning electron microscopy (SEM), quantitative real time PCR (qRT-PCR) and fluorescence in situ hybridization (FISH), we unambiguously demonstrated that this biofilm model is robust and highly reproducible, which is a prerequisite for envisioned high throughput analyses of e.g. anti-biofilm activity of implant surfaces
Our focus was on developing an easy-to-use biofilm model without the need for nutritional supplements that are not manufactured according to uniform quality standards and are of limited availability, such as human saliva and to apply this test system to high content screening
Summary
Dental implants play an important role in maintaining full oral function after tooth loss [1]. Even after successful osseointegration of the implant, periimplant mucositis—bacteria-induced inflammation of the soft tissue around the implant—can occur. If left untreated, this may develop into peri-implantitis. Previous studies have shown that peri-implantitis is caused by polymicrobial communities [14, 15], which grow as sessile microbial communities, so-called biofilms, on dental implant surfaces. Within these biofilms, different bacterial species coexist synergistically, embedded in a selfsecreted, highly structured extracellular matrix [16,17,18]
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