Improvement of an experimental model of oral biofilm

The oral ecosystem presents a great complexity since it can harbor more than 700 different bacterial species. Most of them are organized in a biofilm on both the dental and the mucosal surfaces. Studying this complex environment is of utmost importance because a rupture in its stability can lead to the preeminence of pathogenic microorganisms, causing dental decay, gingivitis and periodontitis1. Furthermore, various studies described the relationship between bacterial species found in the oral biofilm and their presence within other biofilms, such as heart valves biofilm2. Thus, the reproduction of oral biofilms is extremely difficult in vitro. This is due to the complex interrelations between all the different species and the numerous variations of their environment. Besides, growing, harvesting and counting the bacteria are three critical laboratory procedures. Even if in vitro models fail to re-create the complexity of the oral environment, they offer many advantages. They contribute to demonstrate the cariogenic potential of different microorganisms, or the effect of various components on oral biofilms3-6. They also help to identify the strains involved in periodontitis, and test molecules that can fight it7-9. Numerous laboratory models have already been described in the literature: one of our previous works reviewed all experimental models of oral biofilms developed on inert substrates10. Abstract – Objectives: The main aim of our work was to get one step closer to the in vivo conditions. We started from a multispecies static biofilm model containing five different bacteria, implementing specific enhancements. Our second goal was to improve the analysis of such biofilms regarding collection and identification. Material and Methods: We started from a multispecies static model with five oral strains growing on hydroxyapatite discs to improve it on multiple points. We modified culture conditions and added two more strains. We also changed bacteria collection, which evolved from manually scrapping the discs surface to the combination of ultrasonic and mechanical harvesting. In a further another step, we developed a dynamic model implementing the above changes with a continuous supply of medium flow and waste disposal. Different methods have been evaluated to monitor the presence of all the species within the biofilms, and to quantify them: gram staining, PCR, MALDI-TOF-MS, qPCR. Results: The modifications brought to our static model confirmed its reproducibility. Even if improvements need to be made, our dynamic model of oral biofilm is already a good alternative to more sophisticated and expensive models. Conclusions: This new oral biofilm model represents the premises of another way to study the environmental variations effects on bacterial development, its larger application will result in a better understanding of oral health significant factors.