Metagenomic nanopore sequencing is demonstrating potential as a tool for diagnosis of infections directly from clinical samples. We have previously shown nanopore sequencing can be used to determine the causative bacterial species in prosthetic joint infections (PJI). However, to make predictions regarding antimicrobial resistance, human DNA contamination must be reduced so a greater proportion of sequence data corresponds to the microbial portion of the DNA extract. Here, we utilise selective DNA extraction from sonication fluid samples to begin to make predictions regarding antimicrobial resistance in PJI. We investigated host cell DNA depletion with 5% saponin selective human cell lysis followed by nuclease digestion. Subsequently, bacterial cells were mechanically lysed before DNA extraction. Sequencing libraries from samples treated with and without saponin were prepared with a Rapid PCR Barcoding Kit1 and sequenced in multiplexes of 2–8 samples/flowcell on a GridION. Sequencing reads were analysed using the CRuMPIT pipeline and thresholds to indicate presence of a specific bacterial genus/species were investigated. Antimicrobial resistance determinants were detected using previously published sequences specifically for Aim
Method
Culture of multiple periprosthetic tissue samples is the current gold-standard for microbiological diagnosis of prosthetic joint infections (PJI). Additional diagnostic information may be obtained through sonication fluid culture of explants. These current techniques can have relatively low sensitivity, with prior antimicrobial therapy or infection by fastidious organisms particularly influencing culture results. Metagenomic sequencing has demonstrated potential as a tool for diagnosis of bacterial, viral and parasitic infections directly from clinical samples, without the need for an initial culture step. We assessed whether metagenomic sequencing of DNA extracts from sonication fluid can provide a sensitive tool for diagnosis of PJI compared to sonication fluid culture. We compared metagenomic sequencing with standard aerobic and anaerobic culture in 97 sonication fluid samples from prosthetic joint and other orthopaedic device-related infections. Sonication fluids were filtered to remove whole human cells and tissue debris, then bacterial cells were mechanically lysed before DNA extraction. DNA was sequenced and sequencing reads were taxonomically classified using Kraken. Using 50 derivation samples, we determined optimal thresholds for the number and proportion of bacterial reads required to identify an infection and confirmed our findings in 47 independent validation samples.Aim
Method
