Key topographic parameters driving surface adhesion of Porphyromonas gingivalis

Abstract

Dental implant failure is primarily due to peri-implantitis, a consequence of bacterial biofilm formation. Bacterial adhesion is strongly linked to micro-/nano-topographies of a surface; thus an assessment of surface texture parameters is essential to understand bacterial adhesion. In this study, mirror polished titanium samples (Ti6Al4V) were irradiated with a femtosecond laser (fs-L) at a wavelength of 1030 nm (infrared) with variable laser parameters (laser beam polarization, number, spacing and organization of the impacts). Images of 3-D topographies were obtained by focal variation microscopy and analyzed with MountainsMap software to measure surface parameters. From bacteria associated with peri-implantitis, we selected Porphyromonas gingivalis to evaluate its adhesion on Ti6Al4V surfaces in an in vitro study. Correlations between various surface parameters and P. gingivalis adhesion were investigated. We discovered that Sa value, a common measure of surface roughness, was not sufficient in describing the complexity of these fs-L treated surfaces and their bacterial interaction. We found that Sku, density and mean depths of the furrows, were the most accurate parameters for this purpose. These results provide important information that could help anticipate the bacterial adhesive properties of a surface based on its topographic parameters, thus the development of promising laser designed biofunctional implants.

Figure 1

Surfaces visualization and associated laser parameters. SEM images of polished and LIPSS-textured Ti6Al4V surfaces.

Figure 2

Evaluation of P. gingivalis adhesion on the different surfaces. (a) Representative fluorescence images of calcein stained P. gingivalis 48 h postseeding on partially textured samples. (b) Graph presenting the fluorescence quantification as mean ± SEM. n = 30 area/group; t-test compared to polished control; ***p = 0.0003; ****p < 0.0001. (c) SEM images of P. gingivalis on partially textured surfaces.

Figure 3

Surface topographies and associated parameters. Graphical representation of the correlation between P. gingivalis biofilm formation and Sa (a), Sp (b), Sv (c), Ssk (d) or Sku (e) with the Spearman's rank-order correlation and associated p-value. (f) 3-D representation of surface topographies.

Figure 4

Hybrid parameters. Graphical representation of the correlation between P. gingivalis adhesion and Sdq or Sdr with the Spearman's rank-order correlation and associated p-value.

Figure 5

Furrows characterization. (A) Qualitative rendering of the furrows. (B) Graphical representation of the correlation between P. gingivalis adhesion and density of furrows or mean furrows depth with the Spearman's rank-order correlation and associated p-value.