Objectives: The term sulfate-reducing bacteria (SRB) describes strictly anaerobic microbes that accomplish the dissimilatory reduction of sulfate to hydrogen sulfide. The 16S rDNA sequence showed a high similarity of 99.7% with the 16S rDNA of the proposed species 'Desulfovibrio fairfieldensis'. The aim of this study was to examine in an in vitro assay the colonization of 2 types of resorbable membranes for guided tissue regeneration by strains of SRB and P.gingivalis. Material and Methods: Pieces of membranes were submerged in batchcultures of Desulfovibrio spp. and P. gingivalis FDC381 in reduced growth medium specific for SRB or PY medium, and incubated for 1-8 days of lagtime. The dry weight of the membranes was determined after 2, 5 hours and 3, 6, 12, and 24 weeks. After incubation, membranes were prepared for SEM analysis. Bacterial density was measured semiquantitatively at 50 x magnification for selecting region of interests (ROI). Five 20x25µm fields were randomly selected for each specimen using the software system Imaging PC for Windows. Results: SEM analysis revealed differences in the accumulation of SRB strains and P. gingivalis on the 2 types of investigated membranes. The deep SRB invasion at the 3d week and frequent presence of internal bacteria at the 6th week on the PLA with copolymer membranes underlined the differences obtained by quantitative evaluation of bacterial density. The difference between the bacterial layers was statistically significant (Kruskal-Wallis-Test, p=0.05). Conclusions: The present investigation examined the relationship between the degrees of PLA membrane degradation and the amount of SRB colonization observed after up to 12 weeks undisturbed growth. The bacterial cells adhering to the membranes surface was depended on the degree of membranes mass loss over the time interval. Interestingly, the results suggest an active role of SRB in the degradation of the resorbable PLA membranes. Keywords: in vitro-colonization, Sulfat-Reducing Bacteria (SRB), resorbable GTR membranes, quantitative SEM-evaluation