Identification of bacteria causing tissue infections can be comprehensive and, in the cases of non- or slow-growing bacteria, near impossible with conventional methods. Performing shotgun metagenomic sequencing on bacterial DNA extracted directly from the infected tissue may improve time to diagnosis and targeted treatment considerably. However, infected tissue consists mainly of human DNA (hDNA) which hampers bacterial identification. In this proof of concept study, we present a modified version of the Ultra-Deep Microbiome Prep kit for DNA extraction procedure, removing additional human DNA. Tissue biopsies from 3 patients with orthopedic implant-related infections containing varying degrees of Staphylococcus aureus were included. Subsequent DNA shotgun metagenomic sequencing using Oxford Nanopore Technologies’ (ONT) MinION platform and ONTs EPI2ME WIMP and ARMA bioinformatic workflows for microbe and antibiotic resistance genes identification, respectively. The modified DNA extraction protocol led to an additional ~10-fold reduction of human DNA while preserving S. aureus DNA. Including the DNA sequencing and bioinformatics analyses, the presented protocol has the potential of identifying the infection-causing pathogen in infected tissue within 7 hours after biopsy. However, due to low number of S. aureus reads, positive identification of antibiotic resistance genes was not possible.

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Outbreak investigations are essential to control and prevent the dissemination of pathogens. This study developed and validated a complete analysis protocol for faster and more accurate surveillance and outbreak investigations of antibiotic-resistant microbes based on Oxford Nanopore Technologies (ONT) DNA whole-genome sequencing. The protocol was developed using 42 methicillin-resistant Staphylococcus aureus (MRSA) isolates identified from former well-characterized outbreaks. The validation of the protocol was performed using Illumina technology (MiSeq, Illumina). Additionally, a real-time outbreak investigation of six clinical S. aureus isolates was conducted to test the ONT-based protocol. The suggested protocol includes: (1) a 20 h sequencing run; (2) identification of the sequence type (ST); (3) de novo genome assembly; (4) polishing of the draft genomes; and (5) phylogenetic analysis based on SNPs. After the sequencing run, it was possible to identify the ST in 2 h (20 min per isolate). Assemblies were achieved after 4 h (40 min per isolate) while the polishing was carried out in 7 min per isolate (42 min in total). The phylogenetic analysis took 0.6 h to confirm an outbreak. Overall, the developed protocol was able to at least discard an outbreak in 27 h (mean) after the bacterial identification and less than 33 h to confirm it. All these estimated times were calculated considering the average time for six MRSA isolates per sequencing run. During the real-time S. aureus outbreak investigation, the protocol was able to identify two outbreaks in less than 31 h. The suggested protocol enables identification of outbreaks in early stages using a portable and low-cost device along with a streamlined downstream analysis, therefore having the potential to be incorporated in routine surveillance analysis workflows. In addition, further analysis may include identification of virulence and antibiotic resistance genes for improved pathogen characterization.

Conventional culture-based diagnostics of orthopaedic-implant-associated infections (OIAIs) are arduous. Hence, the aim of this study was to evaluate a culture-independent, rapid nanopore-based diagnostic protocol with regard to (a) pathogen identification, (b) time to pathogen identification, and (c) identification of antimicrobial resistance (AMR). This prospective proof-of-concept study included soft tissue biopsies from 32 patients with OIAIs undergoing first revision surgery at Akershus University Hospital, Norway. The biopsies were divided into two segments. Nanopore shotgun metagenomic sequencing and pathogen and antimicrobial resistance gene identification using the EPI2ME analysis platform (Oxford Nanopore Technologies) were performed on one segment. Conventional culture-based diagnostics were performed on the other. Microbial identification matched in 23/32 OIAI patients (72%). Sequencing detected additional microbes in 9/32 patients. Pathogens detected by culturing were identified by sequencing within a median of 1 h of sequencing start [range 1–18 h]. Phenotypic AMR was explained by the detection of resistance genes in 11/23 patients (48%). Diagnostics of OIAIs using shotgun metagenomics sequencing are possible within 24 h from biopsy using nanopore technology. Sequencing outperformed culturing with respect to speed and pathogen detection where pathogens were at sufficient concentration, whereas culture-based methods had an advantage at lower pathogen concentrations. Sequencing-based AMR detection may not yet be a suitable replacement for culture-based antibiotic susceptibility testing.