Improved diagnosis of prosthetic joint infection using a marine nuclease

Abstract

Prosthetic joint infection is devastating for the patient and costly to the healthcare provider. Key to the treatment of prosthetic joint infection is the identification of the causative organism. This can be challenging since biofilm encapsulated bacteria can establish themselves on the implant surface avoiding standard microbiological detection. Focus, therefore has fallen on increasing the yield of bacteria from the explanted implant surface to make a diagnosis. The marine nuclease NucB is a novel enzyme capable of digesting eDNA a component of the biofilm matrix, utilised by causal organisms in prosthetic joint infection. Use of NucB results in the release of bacterial cells from the biofilm, allowing them to be brought into planktonic suspension, thereby potentially aiding in their identification and the diagnosis of infection. To evaluate the potential of NucB to improve the diagnosis of prosthetic joint infection, a biofilm model was established initially using a microtiter plate system, then subsequently a series of simulated prosthetic implant surfaces using isolates of Staphylococcus epidermidis and Staphylococcus aureus. Finally, the ability of NucB to release bacteria from biofilms formed on explanted joint replacements from patients undergoing revision arthroplasty surgery was evaluated. Results demonstrated that NucB produced a significant increase in the number of bacteria released when compared to controls and was, for the majority of isolates evaluated, comparable to sonication, another technique used to increase the yield of bacteria from prosthetic implant surfaces. Results from the evaluation of the explanted joint replacements demonstrated that NucB was comparable to sonication and also compatible with standard microbiological processing systems within the UK National Health Service. This has work demonstrated that NucB is effective at increasing the bacterial yield from biofilm encapsulated bacteria and has the potential to improve the accuracy of diagnosis in prosthetic joint infection, thus improving patient care.