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Bone & Joint Research
Vol. 8, Issue 8 | Pages 367 - 377
1 Aug 2019
Chen M Chang C Chiang-Ni C Hsieh P Shih H Ueng SWN Chang Y

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


Bone & Joint Research
Vol. 8, Issue 4 | Pages 179 - 188
1 Apr 2019
Chen M Chang C Yang L Hsieh P Shih H Ueng SWN Chang Y

Objectives

Prosthetic joint infection (PJI) diagnosis is a major challenge in orthopaedics, and no reliable parameters have been established for accurate, preoperative predictions in the differential diagnosis of aseptic loosening or PJI. This study surveyed factors in synovial fluid (SF) for improving PJI diagnosis.

Methods

We enrolled 48 patients (including 39 PJI and nine aseptic loosening cases) who required knee/hip revision surgery between January 2016 and December 2017. The PJI diagnosis was established according to the Musculoskeletal Infection Society (MSIS) criteria. SF was used to survey factors by protein array and enzyme-linked immunosorbent assay to compare protein expression patterns in SF among three groups (aseptic loosening and first- and second-stage surgery). We compared routine clinical test data, such as C-reactive protein level and leucocyte number, with potential biomarker data to assess the diagnostic ability for PJI within the same patient groups.