Rapid Nanopore Sequencing to Identify Bacteria Causing Prosthetic Joint Infections

<b>Background/Objectives:</b> 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. <b>Methods</b>: 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. <b>Results</b>: 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%). <b>Conclusions</b>: Nanopore sequencing has the potential to aid identification of bacteria causing prosthetic joint infection and may be useful as a supplementary diagnostic tool.

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Publication Details

Journal
Antibiotics
Published
2025-08-31
DOI
https://doi.org/10.3390/antibiotics14090879
Primary Topic
Orthopedic Infections and Treatments
Type
article
Field-Weighted Citation Impact
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article

Rapid Nanopore Sequencing to Identify Bacteria Causing Prosthetic Joint Infections

Hollie Wilkinson, Helen S. McCarthy, Karina T. Wright, Jade Perry et al.
Antibiotics
Orthopedic Infections and Treatments
article

Rapid Nanopore Sequencing to Identify Bacteria Causing Prosthetic Joint Infections

Hollie Wilkinson, Helen S. McCarthy, Karina T. Wright, Jade Perry, Benjamin Burston, Rob Townsend, Charlotte Hulme, Niall Steele, Paul Cool
article en

Abstract

<b>Background/Objectives:</b> 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. <b>Methods</b>: 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. <b>Results</b>: 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%). <b>Conclusions</b>: Nanopore sequencing has the potential to aid identification of bacteria causing prosthetic joint infection and may be useful as a supplementary diagnostic tool.

AntibioticsVol. 14(9)
Robert Jones and Agnes Hunt Orthopaedic Hospital (GB), Sheffield Teaching Hospitals NHS Foundation Trust (GB), Keele University (GB)
Openalex Percentile: Top 63%
Orthopedic Infections and Treatments
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