Direct Detection and Identification of Prosthetic Joint Pathogens in Synovial Fluid (SF) by Metagenomic Shotgun Sequencing. (4th October 2017)

• Record Type: Journal Article
• Authors: Ivy, Morgan; Thoendel, Matthew; Jeraldo, Patricio; Greenwood-Quaintance, Kerryl; Hanssen, Arlen D; Abdel, Matthew; Chia, Nicholas; Yao, Janet; Tande, Aaron; Mandrekar, Jayawant; Patel, Robin
• Is Part Of: Open forum infectious diseases. Volume 4(2017)Supplement 1
• Page Start: S32
• Page End: S32
• Publication Date: 2017-10-04
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofx162.078
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: Detection and identification of microorganism(s) involved in periprosthetic joint infection (PJI) can inform surgical management and directed antibiotic therapy. Metagenomic shotgun sequencing is a powerful tool with the potential to change how many PJIs are diagnosed as it allows direct detection and identification of pathogens in clinical specimens. In the largest series to date, we utilized a metagenomics-based approach applied to SF to define potential microbial etiologies of failed total knee arthroplasties (TKAs). Methods: Synovial fluid was collected from 112 failed TKAs [74 PJI and 38 aseptic implant failure (AF)] via preoperative arthrocentesis. Cell count and differential, standardized culture and DNA-based metagenomic shotgun sequencing were performed. Human DNA was depleted using the MolYsis basic kit prior to DNA extraction, whole genome amplification, and sequencing. Taxonomic assignment of reads and pathogen identification was achieved using a pipeline incorporating k-mer- and marker gene-based classification software. A scheme for analysis and filtration of false-positives was created and applied, incorporating cut-offs for the number of reads, quality scores, and coverage across a reference genome. Patients were classified as having PJI using the IDSA criteria and expert review. Analyses were recorded as percent agreement, with 95% confidence intervals (CI), of metagenomics to SF culture. Results: Metagenomic analysis identified the known pathogen in 54 (90%) (CI, 79.5%–96.2%) of the 60 culture-positive PJIs analyzed and one (2%) (CI, 0.0%–8.9%) potential polymicrobial infection not detected by culture. For the 14 culture-negative PJIs tested, metagenomics showed 79% (CI, 49.2%–95.3%) agreement for negative findings; potential pathogens were identified in three (21%) (CI, 4.7%–50.8%) culture-negative PJI cases, with one being polymicrobial. Of the 37 culture-negative AF cases, metagenomics showed 97% (CI, 85.8%–99.9%) agreement with negative culture and identified one (3%) (CI, 0.0%–14.2%) potential pathogen. For the one culture-positive AF case, metagenomic results were negative, suggesting possible culture contamination. Conclusion: Metagenomic shotgun sequencing performed on SF can be used to diagnose PJI and may be particularly useful for culture-negative PJI. Disclosures: R. Patel, ASM: Board Member, None; CD Diagnostics, BioFire, Curetis, Merck, Hutchison Biofilm Medical Solutions, Accelerate Diagnostics, Allergan, and The Medicines Company: Grant Investigator, Grant recipient; Curetis: Consultant, Monies paid to my employer; A patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, and a patent on an anti-biofilm substance issued: Patents, Patents, any money is paid to my employer; Actelion: DSMB, Money paid to my employer; ASM and IDSA: Editor's stipends, Editor's stipends; NBME, Up-to-Date and the Infectious Diseases Board Review Course: NBME, Up-to-Date and the Infectious Diseases Board Review Course, Honoraria; Roche, ASM, and IDSA: Travel reimbursement, Travel reimbursement