Article ; Online: Identification of prosthetic joint infections with 16S amplicon metagenomic sequencing - comparison with standard cultivation approach.
Diagnostic microbiology and infectious disease
2024 Volume 109, Issue 1, Page(s) 116188
Abstract: Prosthetic joint infections (PJIs) are commonly diagnosed via culture-based methods, which may miss hard-to-grow pathogens. This study contrasts amplicon metagenomic sequencing (16S AS) with traditional culture techniques for enhanced clinical decision- ... ...
Abstract | Prosthetic joint infections (PJIs) are commonly diagnosed via culture-based methods, which may miss hard-to-grow pathogens. This study contrasts amplicon metagenomic sequencing (16S AS) with traditional culture techniques for enhanced clinical decision-making. We analyzed sonicate fluid from 27 patients undergoing revision arthroplasty using both methods, emphasizing the distinction between contaminants and true positives. Our findings show moderate agreement between the two methods, with a Cohen's kappa of 0.490, varying across bacterial genera (Cohen's kappa -0.059 to 1). The sensitivity of 16S AS compared to culture was 81% (95% CI, 68% to 94%). Sequencing revealed greater microbial diversity, including anaerobic genera like Anaerococcus and Citrobacter. Interestingly, several culture-negative PJI samples showed diverse bacteria via 16S AS. Despite rigorous controls and algorithms to eliminate contaminants, confirming bacteria presence with 16S AS remains a challenge. This highlights the need for improved PJI diagnostic methods, while also pointing out the limitations of next-generation sequencing (NGS) as a clinical diagnostic tool. |
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MeSH term(s) | Humans ; Arthritis, Infectious/diagnosis ; Bacteria/genetics ; Prostheses and Implants ; Arthroplasty ; High-Throughput Nucleotide Sequencing ; Prosthesis-Related Infections/diagnosis ; Prosthesis-Related Infections/microbiology ; Sensitivity and Specificity ; RNA, Ribosomal, 16S/genetics |
Chemical Substances | RNA, Ribosomal, 16S |
Language | English |
Publishing date | 2024-01-17 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 604920-5 |
ISSN | 1879-0070 ; 0732-8893 |
ISSN (online) | 1879-0070 |
ISSN | 0732-8893 |
DOI | 10.1016/j.diagmicrobio.2024.116188 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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