Oral Presentation ESA-SRB-ANZBMS 2024 in conjunction with ENSA

Rapid Molecular Detection and Quantification of Bacterial Load in Periprosthetic Joint Infection (#118)

Qi Sun 1 , Dzenita Muratovic 1 , Kimberley Huynh 1 , Bogdan Solomon 1 2 , Paul H. Anderson 3 , Dongqing Yang 1 , Gerald J. Atkins 1
  1. Centre for Orthopaedic & Trauma Research, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
  2. Department of Orthopaedics and Trauma, Royal Adelaide Hospital, Adelaide, South Australia, Australia
  3. Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia

Identification of pathogens is critical for the diagnosis and targeted treatment of periprosthetic joint infection (PJI). Bacterial culture of intraoperative tissue is the current gold-standard approach; however, this has low sensitivity, contributing to a high false-negative rate in clinical PJI of approximately 33%, while positive results may take up to 14 days. The purpose of this study was to develop a method for the rapid molecular evaluation of bacterial load in in vitro, pre-clinical and clinical settings. First, we employed an established PJI/osteomyelitis-relevant model using osteocyte-like differentiated SaOS2 cells with S. aureus, to demonstrate the significant discrepancy between colony-forming-unit (CFU) counts and molecular quantification of bacterial genome copy number in vitro. Secondly, we utilised a mouse model of PJI using trans-tibial implantation of stainless-steel pins coated with S. aureus to examine bacterial load in an in vivo infection context. To provide insight into the role of initial bacterial load in the infection dynamics, we quantified bacterial attachment to the implant either by culture or by digital droplet PCR (ddPCR) of a number of S. aureus strains, which again demonstrated the superiority of the molecular approach. Acute bone tissue bacterial load was examined after 4-days. Tibiae were decalcified, paraffin-embedded, sectioned, then subjected to efficient DNA isolation and ddPCR, quantifying both bacterial and host genome copy number. Finally, as recently published1, we showcased the application of ddPCR on DNA extracted from similarly treated bone specimens of PJI patients with unknown pathogens. Together with PCR-based DNA sequencing, we were able to quantify and identify pathogens within 48h of specimen retrieval. This study provides new insights for the design and analysis of experimental infection models and offers a new approach for the molecular detection and quantification of unknown pathogens in PJI and potentially other infectious diseases.

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  1. 1. Sun Q et al. eLife. 2024, 13:RP93698