Objectives: Pathogen identification is crucial for the diagnosis and management of periprosthetic joint infection (PJI). Although culturing methods are the foundation of pathogen detection in PJI, false-negative results often occur. Oxford nanopore sequencing (ONS) is a promising alternative for detecting pathogens and providing information on their antimicrobial resistance (AMR) profiles, without culturing.
Methods: To evaluate the capability of metagenomic ONS (mONS) in detecting pathogens from PJI samples, both metagenomic next-generation sequencing (mNGS) and mONS were performed in 15 osteoarticular samples from nine consecutive PJI patients according to the modified Musculoskeletal Infection Society (MSIS) criteria. The sequencing data generated from both platforms were then analyzed for pathogen identification and AMR detection using an in-house-developed bioinformatics pipeline.
Results: Our results showed that mONS could be applied to detect the causative pathogen and characterize its AMR features in fresh PJI samples. By real-time sequencing and analysis, pathogen identification and AMR detection from the initiation of sequencing were accelerated.
Conclusion: We showed proof of concept that mONS can function as a rapid, accurate tool in PJI diagnostic microbiology. Despite efforts to reduce host DNA, the high proportion of host DNA was still a limitation of this method that prevented full genome analysis.
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| http://dx.doi.org/10.1016/j.ijid.2020.05.044 | DOI Listing |
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