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Using nanopore sequencing to identify bacterial infection in joint replacements: a preliminary study
Hollie Wilkinson1,2, Jamie McDonald3, Helen S McCarthy1,2
1Centre for Regenerative Medicine, School of Pharmacy and Bioengineering, Keele University, Keele, UK.
Abstract:
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.
Insights
Third-generation genomic sequencing accurately identifies bacteria causing prosthetic joint infections (PJIs) during revision surgery. While rapid bacterial identification is feasible, predicting antibiotic resistance requires further research.
Area of Science:
- Microbiology
- Genomics
- Orthopedic Surgery
Background:
- Prosthetic joint infections (PJIs) are a significant complication following joint replacement surgery.
- Accurate and rapid identification of causative bacteria is crucial for effective treatment.
- Current diagnostic methods, such as microbiological cultures, can be time-consuming.
Purpose of the Study:
- To evaluate the utility of third-generation genomic sequencing for identifying bacterial species in PJIs during revision surgery.
- To assess the feasibility of rapid bacterial identification using Nanopore sequencing.
- To explore the potential of genomic data for predicting antibiotic resistance in PJIs.
Main Methods:
- Prosthetic fluid samples were collected from patients undergoing revision surgery for PJIs and controls.
- Genomic sequencing was performed using Oxford Nanopore Technologies' MinION device.
- Bioinformatic pipelines (BLAST, Kraken2, MDS) and computational tools (ResFinder, AMRFinderPlus, CARD) were employed for bacterial identification and resistance prediction.
Main Results:
- Bioinformatic analysis pipelines successfully identified bacteria, consistent with standard microbiological cultures.
- Nanopore sequencing and genomic classification were completed within the surgical timeframe (2-3 hours).
- Antibiotic resistance prediction was not achieved within the clinically relevant timeframe, likely due to short read length and low read depth.
Conclusions:
- Genomic sequencing is a viable method for identifying bacterial species in infected joint replacements.
- The rapid turnaround time of Nanopore sequencing is suitable for intraoperative use.
- Further optimization is needed to enable timely prediction of antibiotic resistance using genomic sequencing.
