de novo analysis of prosthetic joint infection microbiata using metagenomics

Following the increase in widespread applications of joint prosthesis surgeries around the world, an increase in prosthetic joint infection (PJI) rates has also been observed. While the infection rate in first-time surgeries are around 2%, this rate is elevated in revision surgeries. Use of orthopedic prostetic implants employed in arthralgia governed by other diseases and in limitations of movement will increase due to enlarging elderly and obese population. While the majority of culture positive PJI cases can be treated using multidrugs, in 5%-35% PJI cases conventional methods fail to isolate pathogens. While this causes difficulties in treatment, it results in the confusion of PJI with another surgical complication: aseptic implant failure. In addition, due to the existence of sub populations of bacteria which plays a role in etiology and/or existence of polymicrobial pathogens and mechanisms such as biofilm formation lead to failure in treatment. For that reason, new diagnostic approaches that can identify organisms which participate in PJI etiology and cannot be identified using conventional methods, reveal antibiotic resistance mechanisms to assist the treatment strategies are becoming crucial day by day.The goal of this project was to understand the etiology of PJI's with diagnostic and treatment challenges via pathobiome analysis, thus to improve diagnosis and to assist treatment.