RT Journal Article SR Electronic T1 Real-time analysis of nanopore-based metagenomic sequencing from orthopaedic device infection JF bioRxiv FD Cold Spring Harbor Laboratory SP 220616 DO 10.1101/220616 A1 Nicholas D Sanderson A1 Teresa L Street A1 Dona Foster A1 Jeremy Swann A1 Bridget L. Atkins A1 Andrew J. Brent A1 Martin A. McNally A1 Sarah Oakley A1 Adrian Taylor A1 Tim E A Peto A1 Derrick Crook A1 David W Eyre YR 2017 UL http://biorxiv.org/content/early/2017/11/17/220616.abstract AB Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we compare direct-from-clinical-sample metagenomic Illumina sequencing with Nanopore sequencing, and report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections.DNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination.The majority of DNA classified (>90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing.We demonstrate initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data. The high proportion of human DNA in extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling.