Objectives. Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect unculturable, unsuspected, and unviable pathogens. In this study, we investigated the use of 16S rRNA metagenomics for detection of bacterial pathogens in synovial fluid (SF) from patients with hip or knee PJI. Methods. We analyzed the bacterial composition of 22 SF samples collected from 11 patients with PJIs (first- and second-stage surgery). The V3 and V4 region of bacteria was assessed by comparing the taxonomic distribution of the 16S rDNA amplicons with microbiome sequencing analysis. We also compared the results of bacterial detection from different methods including 16S metagenomics, traditional cultures, and targeted Sanger sequencing. Results. Polymicrobial infections were not only detected, but also characterized at different timepoints corresponding to first- and second-stage exchange arthroplasty. Similar taxonomic distributions were obtained by matching sequence data against SILVA, Greengenes, and The National Center for Biotechnology Information (NCBI). All bacteria isolated from the traditional culture could be further identified by 16S metagenomics and targeted Sanger sequencing. Conclusion. The data highlight 16S rRNA metagenomics as a suitable and promising method to detect and identify infecting bacteria, most of which may be uncultivable. Importantly, the method dramatically reduces turnaround time to two days rather than approximately one week for conventional cultures. Cite this article: M-F. Chen, C-H. Chang, C. Chiang-Ni, P-H. Hsieh, H-N. Shih, S. W. N. Ueng, Y. Chang. Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing. Bone Joint Res 2019;8:367–377. DOI: 10.1302/2046-3758.88.BJR-2019-0003.R2

Aims. The aim of this study was to evaluate the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens from synovial fluid of prosthetic joint infection (PJI) patients. Methods. A group of 75 patients who underwent revision knee or hip arthroplasties were enrolled prospectively. Ten patients with primary arthroplasties were included as negative controls. Synovial fluid was collected for mNGS analysis. Optimal thresholds were determined to distinguish pathogens from background microbes. Synovial fluid, tissue, and sonicate fluid were obtained for culture. Results. A total of 49 PJI and 21 noninfection patients were finally included. Of the 39 culture-positive PJI cases, mNGS results were positive in 37 patients (94.9%), and were consistent with culture results at the genus level in 32 patients (86.5%) and at the species level in 27 patients (73.0%). Metagenomic next-generation sequencing additionally identified 15 pathogens from five culture-positive and all ten culture-negative PJI cases, and even one pathogen from one noninfection patient, while yielding no positive findings in any primary arthroplasty. However, seven pathogens identified by culture were missed by mNGS. The sensitivity of mNGS for diagnosing PJI was 95.9%, which was significantly higher than that of comprehensive culture (79.6%; p = 0.014). The specificity is similar between mNGS and comprehensive culture (95.2% and 95.2%, respectively; p = 1.0). Conclusion. Metagenomic next-generation sequencing can effectively identify pathogens from synovial fluid of PJI patients, and demonstrates high accuracy in diagnosing PJI. Cite this article: Bone Joint Res 2020;9(7):440–449

Aims. This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment. Methods. A retrospective analysis was conducted on 235 patients with BJIs who were treated at our hospital between January 2015 and December 2021. Patients were divided into the no-mNGS group (microbial culture only) and the mNGS group (mNGS testing and microbial culture) based on whether mNGS testing was used or not. Results. A total of 147 patients were included in the no-mNGS group and 88 in the mNGS group. The mNGS group had a higher detection rate of rare pathogens than the no-mNGS group (21.6% vs 10.2%, p = 0.016). However, the mNGS group had lower rates of antibiotic-related complications, shorter hospital stays, and higher infection control rates compared with the no-mNGS group (p = 0.017, p = 0.003, and p = 0.028, respectively), while there was no significant difference in the duration of antibiotic use (p = 0.957). In culture-negative cases, the mNGS group had lower rates of antibiotic-related complications, shorter hospital stays, and a higher infection control rate than the no-mNGS group (p = 0.036, p = 0.033, p = 0.022, respectively), while there was no significant difference in the duration of antibiotic use (p = 0.748). Conclusion. mNGS improves detection of rare pathogens in BJIs. mNGS testing reduces antibiotic-related complications, shortens hospital stay and antibiotic use duration, and improves treatment success rate, benefits which are particularly evident in culture-negative cases. Cite this article: Bone Joint Res 2024;13(8):401–410

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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA.

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This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI) diagnosis, and compare it with that of microbial culture, serum ESR and CRP, synovial white blood cell (WBC) count, and polymorphonuclear neutrophil percentage (PMN%).

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To explore the clinical efficacy of using two different types of articulating spacers in two-stage revision for chronic knee periprosthetic joint infection (kPJI).

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The effect of the gut microbiota (GM) and its metabolite on bone health is termed the gut-bone axis. Multiple studies have elucidated the mechanisms but findings vary greatly. A systematic review was performed to analyze current animal models and explore the effect of GM on bone.

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We aimed to evaluate the utility of ⁶⁸Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with ^99mTc-methylene bisphosphonates (^99mTc-MDP) bone scan.

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Current guidelines consider analyses of joint aspirates, including leucocyte cell count (LC) and polymorphonuclear percentage (PMN%) as a diagnostic mainstay of periprosthetic joint infection (PJI). It is unclear if these parameters are subject to a certain degree of variability over time. Therefore, the aim of this study was to evaluate the variation of LC and PMN% in patients with aseptic revision total knee arthroplasty (TKA).

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Microbiological culture is a key element in the diagnosis of periprosthetic joint infection (PJI). However, cultures of periprosthetic tissue do not have optimal sensitivity. One of the main reasons for this is that microorganisms are not released from the tissues, either due to biofilm formation or intracellular persistence. This study aimed to optimize tissue pretreatment methods in order to improve detection of microorganisms.