Investigating the translational value of Periprosthetic Joint Infection (PJI) models to determine the risk and severity of Staphylococcal biofilms.

Amita Sekar, Yingfang Fan, Peyton Tierney, Madeline McCanne, Parker Jones, Fawaz Malick, Devika Kannambadi, Keith K Wannomae, Nicoletta Inverardi,Orhun Muratoglu,Ebru Oral

bioRxiv : the preprint server for biology(2024)

Cited 0|Views3
No score
Abstract
With the advent of antibiotic-eluting polymeric materials for targeting recalcitrant infections, using preclinical models to study biofilm is crucial for improving the treatment efficacy in periprosthetic joint infections. The stratification of risk and severity of infections is needed to develop an effective clinical dosing framework with better outcomes. Here, using in-vivo and in-vitro implant-associated infection models, we demonstrate that methicillin-sensitive and resistant Staphylococcus aureus (MSSA and MRSA) have model-dependent distinct implant and peri-implant tissue colonization patterns. The maturity of biofilms and the location (implant vs tissue) were found to influence the antibiotic susceptibility evolution profiles of MSSA and MRSA and the models could capture the differing host-microbe interactions in vivo. Gene expression studies revealed the molecular heterogeneity of colonizing bacterial populations. The comparison and stratification of the risk and severity of infection across different preclinical models provided in this study can guide clinical dosing to effectively prevent or treat PJI.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined