Assessing peri-implant bacterial community structure
The oral cavity is an exceptionally complex habitat that harbors a large number of microorganisms. Oral microbiota comprises polymicrobial communities shaped by mutualistic coevolution with the host, contributing to homeostasis and regulating immune function. Nevertheless, dysbiosis of oral bacterial communities is associated with a number of clinical symptoms that ranges from infections to oral cancer. Peri-implant diseases are biofilm-associated inflammatory conditions affecting the soft and hard tissues around dental implants. Therefore, the detection of early symptoms of infection are essential to prevent disease progression and implant failure. Since oral microbiota is also strongly associated with peri-implant health status, the study of oral bacterial communities may be a promising approach for monitoring peri-implant health.  The aim of this study was to evaluate the effect of different oral sampling approaches on metagenomic profiles of peri-implant bacterial communities as revealed by 16S rRNA sequencing. With the aim of selecting an appropriate microbiome sampling procedure for characterizing transepithelial abutment biofilms, next generation sequencing was used for characterizing the bacterial communities of obtained by three different sample sampling types strategies two months after transepithelial abutment placement: adjacent periodontal crevicular fluid (ToCF),  crevicular fluid from transepithelial abutment (TACF) and transepithelial abutment (TA).  Significant differences in multiple alpha diversity indices were detected at both the OTU and the genus level between different sampling procedures. Differentially abundant taxa were detected between sample collection strategies, including peri-implant health and disease related taxa. At the community level significant differences were also detected between TACF and TA and also between TA and ToCF. Moreover, differential network properties and association patterns were identified.  These results suggest that microbiome profiles could assist peri-implant health surveillance. However, the selection of sample collection strategy can significantly affect the community composition and structure.