This project investigates if third-generation genomic sequencing can be used to identify the species of bacteria causing prosthetic joint infections (PJIs) at the time of revision surgery. Samples of prosthetic fluid were taken during revision surgery from patients with known PJIs. Samples from revision surgeries from non-infected patients acted as negative controls. Genomic sequencing was performed using the MinION device and the rapid sequencing kit from Oxford Nanopore Technologies. Bioinformatic analysis pipelines to identify bacteria included Basic Local Alignment Search Tool, Kraken2 and MinION Detection Software, and the results were compared with standard of care microbiological cultures. Furthermore, there was an attempt to predict antibiotic resistance using computational tools including ResFinder, AMRFinderPlus and Comprehensive Antibiotic Resistance Database. Bacteria identified using microbiological cultures were successfully identified using bioinformatic analysis pipelines. Nanopore sequencing and genomic classification could be completed in the time it takes to perform joint revision surgery (2–3 h). Genomic sequencing in this study was not able to predict antibiotic resistance in this time frame, this is thought to be due to a short-read length and low read depth. It can be concluded that genomic sequencing can be useful to identify bacterial species in infected joint replacements. However, further work is required to investigate if it can be used to predict antibiotic resistance within clinically relevant timeframes.

There is currently no "gold-standard" method to diagnose prosthetic joint infections (PJI), and the current practice of using microbiological cultures has many limitations. The identification of the bacterial species causing the infection is crucial to guide treatment; therefore, a robust method needs to be developed. Here, we attempt to use genomic sequencing with the MinION device from Oxford Nanopore Technologies to identify the species of bacteria causing PJI in a 61-year-old male. Genomic sequencing with the MinION presents an opportunity to produce species identification in real-time and at a smaller cost than current methods. By comparing results with standard hospital microbiological cultures, this study suggests that nanopore sequencing using the MinION could be a faster and more sensitive method to diagnose PJI than microbiological cultures.

Background/Objectives: The diagnosis of prosthetic joint infection remains difficult. Microbiological cultures frequently have false-positive and false-negative results. This study investigates whether rapid nanopore sequencing can be used to aid the identification of bacteria causing prosthetic joint infection for more timely identification and treatment. Methods: Nineteen patients who had revision surgery following total joint arthroplasty were included in this study. Of these, 15 patients had an infected joint arthroplasty. All patients had joint fluid aspirated at the time of revision surgery. The DNA was extracted from these fluid aspirates, and rapid nanopore sequencing was performed using the MinION device from Oxford Nanopore Technologies. The sequencing data was trimmed to improve quality and filtered to remove human reads using bioinformatic tools. Genomic sequence classification was performed using the Basic Local Alignment Search Tool. The results were filtered by read length and sequence identity score. The European Bone and Joint Infection Society criteria were used as a standard to identify infected and not infected patients. Confusion tables were used to calculate accuracy and F1 score based on this criteria and the nanopore sequencing results. Results: Microbiological cultures and nanopore sequencing had an accuracy of 68% and 74%, respectively. However, combining both results predicted infection accurately in 94% of cases (F1 score 96%). Conclusions: Nanopore sequencing has the potential to aid identification of bacteria causing prosthetic joint infection and may be useful as a supplementary diagnostic tool.

Aim: Prosthetic joint infection (PJI) is a serious complication following total joint arthroplasty (TJA) and can have devastating consequences if not treated effectively. There is no clear ‘gold standard’ for the diagnosis of PJI, current techniques include blood biochemical markers and microbiological cultures to identify the species of bacteria. Challenges associated with microbiological cultures include inaccurate results and time delays before reporting of results. In the hospital of study, samples of joint fluid and tissue are collected during surgical intervention for PJI and are sent to a partner hospital for microbiological cultures. Results are typically reported back after 7-14 days. Nanopore sequencing is a third-generation genomic sequencing technology designed to facilitate fast, inexpensive, and simple genomic sequencing. This study aims to investigate nanopore sequencing, as a quick and cost-effective method to identify the species of bacteria causing PJI from joint aspirates. Method: Joint fluid aspirates were collected during surgical interventions for PJI. DNA was extracted from these samples and sequenced using the MinION device. Sequencing data was classified using Basic Local Alignment Search Tool (BLAST) against the bacterial database. Sequencing data was filtered by quality parameters such as Phred score. 30 samples of fluid were used for nanopore sequencing (26 PJI-positive and 4 controls), based on clinical definitions of infection. Clinical assessments included blood biochemical markers (CRP, ESR), histology, physical signs (e.g., redness, swelling) and multi-disciplinary team (MDT) decision. The MDT decision was used as the clinical decision of infection. Results from nanopore sequencing and microbiological cultures were compared with clinical assessments. Results: Contingency tables were made to compare nanopore sequencing with the clinical assessment of patients and to compare microbiological cultures with the clinical decision of patients. Combining the results from nanopore sequencing with microbiological cultures gave an accuracy of 0.89, positive predictive value (PPV) of 0.92, recall (sensitivity) of 0.96 and F1 score of 0.94. The accuracy for microbiological cultures alone was 0.62. Conclusions: Nanopore sequencing shows promise as an additional test in diagnosing PJI, particularly when cultures are negative. The advantage for the use of nanopore sequencing in the diagnosis of PJI is the turn-around time of results compared to microbiological cultures. This could have implications with reducing hospital stays, length of treatment and time frames between the first and second stage of a two-stage prosthetic exchange. This may improve patient outcomes and reduced treatment costs. Further studies could solidify its role in routine PJI diagnosis.